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Rochester
GP: 82 | W: 38 | L: 36 | OTL: 8 | P: 84
GF: 316 | GA: 329 | PP%: 24.38% | PK%: 75.35%
DG: Yanick Morneau | Morale : 50 | Moyenne d’équipe : N/A
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Centre de jeu
Grand Rapids
27-45-10, 64pts
7
FINAL
3 Rochester
38-36-8, 84pts
Team Stats
L1SéquenceW1
16-23-2Fiche domicile18-20-3
11-22-8Fiche domicile20-16-5
4-6-0Derniers 10 matchs7-3-0
3.57Buts par match 3.85
4.49Buts contre par match 4.01
23.64%Pourcentage en avantage numérique24.38%
74.75%Pourcentage en désavantage numérique75.35%
Rochester
38-36-8, 84pts
2
FINAL
1 Cleveland
40-34-8, 88pts
Team Stats
W1SéquenceOTL1
18-20-3Fiche domicile23-17-1
20-16-5Fiche domicile17-17-7
7-3-0Derniers 10 matchs6-2-2
3.85Buts par match 4.27
4.01Buts contre par match 4.09
24.38%Pourcentage en avantage numérique25.93%
75.35%Pourcentage en désavantage numérique74.72%
Meneurs d'équipe
Buts
Josh Norris
30
Passes
Ilya Lyubushkin
54
Points
Josh Norris
71
Plus/Moins
Ilya Lyubushkin
29
Victoires
Stuart Skinner
19
Pourcentage d’arrêts
Stuart Skinner
0.921

Statistiques d’équipe
Buts pour
316
3.85 GFG
Tirs pour
3566
43.49 Avg
Pourcentage en avantage numérique
24.4%
88 GF
Début de zone offensive
40.8%
Buts contre
329
4.01 GAA
Tirs contre
3825
46.65 Avg
Pourcentage en désavantage numérique
75.4%%
87 GA
Début de la zone défensive
42.9%
Informations de l'équipe

Directeur généralYanick Morneau
EntraîneurBrad Shaw
DivisionNord
ConférenceConference est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,872
Billets de saison300


Informations de la formation

Équipe Pro19
Équipe Mineure20
Limite contact 39 / 50
Espoirs40


Historique d'équipe

Saison actuelle38-36-8 (84PTS)
Historique117-101-29 (0.474%)
Apparitions en séries éliminatoires 1
Historique en séries éliminatoires (W-L)3-4
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
1Kevin HayesXX100.0080409678908596738368756882636056500X03012,500,000$
2Marcus KrugerXXX100.00622997686976936590656664776362325000323750,000$
3Josh NorrisX98.0087359290909495778874796789414279500X0231900,000$
4Andrew ShawXX100.00674086767585936478646964775855365000301900,000$
5Dominik KahunXX100.006627988481869177747375658451466650002621,750,000$
6Nick MerkleyXX100.007431928379798879767274648144416250002511,100,000$
7Sven BaertschiXX100.00692899847986897373707164805847535000291850,000$
8AJ Greer (R)X100.00857065728870956870677067755050565000231500,000$
9Gabriel Vilardi (R)XX100.00743094789083897682727765854242795000222900,000$
10Ilya LyubushkinX97.00883269768584875150554893765959495000281975,000$
11Julian MelchioriX100.00723768629782904950504886775858425000302825,000$
12Dan GirardiX100.0069308049877385495049488673919915000382750,000$
13Martin MarincinX100.007431766995798548505045937267633750003021,100,000$
14Brendan GuhleX100.00702795868881724070394181764947535000242500,000$
15Owen Power (R)X100.00762588849494955750654990772929895000193900,000$
Rayé
1Dakota Joshua (R)XXX96.00935081718775967370737274755353605000261500,000$
2Lucas RaymondX96.00832798988291958573798261943230905000202900,000$
MOYENNE D’ÉQUIPE99.2476358777868390656964647479535255500
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
1Scott Darling97.0057938187748886828180766969535000332750,000$
Rayé
1Stuart Skinner (R)100.0068989084768787878780704242825000232500,000$
MOYENNE D’ÉQUIPE98.506396868675888785848073565668500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Brad Shaw68747071878773CAN571500,000$


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
1Josh NorrisRochester (BUF)C52304171104551391402616518311.49%19121623.39911204517630381643253.37%199000011.1713001715
2Max WillmanBuffaloC/LW68263864-10500100142283661789.19%11119117.5261824601910008524047.27%194400001.0701000441
3Ilya LyubushkinRochester (BUF)D7895463291341017675191631174.71%156170221.8351419832211121239110%000000.7400020112
4Dominik KahunRochester (BUF)LW/RW63224062912033105304912427.24%19139222.10613196621700051690148.66%40900000.8923000034
5Tobias RiederBuffaloLW/RW44253358417544662295817810.92%2297722.22109196716300031272138.01%17100011.1903001521
6Martin MarincinRochester (BUF)D78944531184012089174601065.17%185180923.2051217822710002226010%000000.5900000002
7Sven BaertschiRochester (BUF)LW/RW48153651-21002877186351398.06%584517.6231316311290001452058.87%12400001.2101000115
8Gabriel VilardiRochester (BUF)C/RW5321295002007790223741699.42%9120522.75611174717800091722252.71%77400010.8303000323
9Owen PowerRochester (BUF)D4616345085206963138396211.59%107115325.077815681490220148400%000000.8700000250
10AJ GreerRochester (BUF)LW82172643-11021017569257772116.61%12119514.584610341090006771044.51%17300000.7213101040
11Dan GirardiRochester (BUF)D73182442-26407853120409015.00%142159721.896814412500002229120%000100.5300000112
12Julian MelchioriRochester (BUF)D78122739-141071515068152381027.89%138149019.1051318722100002171010%000000.5200003023
13Lucas LessioBuffaloLW/RW72122739-81805062183431516.56%14104414.512911331350001131046.43%11200000.7500000000
14Martin FrkBuffaloLW/RW72162036-41805450195421708.21%10101814.15448321160001112451.58%9500100.7111000201
15Miikka SalomakiBuffaloLW/RW7216153103606963137408411.68%3483711.63000010000231156.10%12300000.7400000104
16Jason ZuckerBuffaloLW/RW3482129-160253317253914.65%1059417.4711112531201013331144.74%3800000.9800000110
17Andrew ShawRochester (BUF)C/RW611116274100399913733978.03%1181213.330226320000201052.54%86600000.6600000014
18Kevin HayesRochester (BUF)C/LW2711152612215415998297011.22%648417.9315617600001493156.96%63900001.0700001331
19Marcus KrugerRochester (BUF)C/LW/RW79101424-114019101144261036.94%126808.612027180000132059.49%82700000.7100000013
20Brendan GuhleRochester (BUF)D8291423-25420576511136748.11%128140817.17617411350003149200%000000.3300000000
21Derek MeechBuffaloD7031619-526054394320326.98%11695313.62011417000183000%000000.4000000210
22Lucas RaymondRochester (BUF)RW1081018124052144224518.18%022922.933258310110392047.17%10600001.5700000220
23Dakota JoshuaRochester (BUF)C/LW/RW1029111111530172710257.41%421821.870228310000311048.42%9500001.0100010110
24Nick MerkleyRochester (BUF)C/RW10145-120159359242.86%016816.84112932000001055.00%2000000.5900000000
Statistiques d’équipe totales ou en moyenne13623276079342689555164716553844106927438.51%11702423017.79921742669143003549572294371851.82%850600230.77518137363641
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
1Stuart SkinnerRochester (BUF)40191740.9213.5023804213917680400.8336408534
2Scott DarlingRochester (BUF)34161430.9154.0119742113215610110.62583333620
3Chris DriedgerBuffalo93310.9104.2145600323570100.6005713100
Statistiques d’équipe totales ou en moyenne83383480.9183.7848116330336860611980541254


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 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
AJ GreerRochester (BUF)LW231998-09-02 22:24:56Yes208 Lbs6 ft3NoNoNoNo1Pro & Farm500,000$2,924$0$0$No
Andrew ShawRochester (BUF)C/RW301991-07-20No195 Lbs5 ft10NoNoNoNo1Pro & Farm900,000$5,263$0$0$NoLien
Brendan GuhleRochester (BUF)D241997-07-29 08:04:16No197 Lbs6 ft2NoNoNoNo2Pro & Farm500,000$2,924$0$0$No500,000$Lien
Dakota JoshuaRochester (BUF)C/LW/RW261996-05-15 08:36:56Yes206 Lbs6 ft3NoNoNoNo1Pro & Farm500,000$2,924$0$0$NoLien
Dan GirardiRochester (BUF)D381984-04-28No212 Lbs6 ft1NoNoNoNo2Pro & Farm750,000$4,386$0$0$No750,000$Lien
Dominik KahunRochester (BUF)LW/RW261995-07-02No176 Lbs5 ft11NoNoNoNo2Pro & Farm1,750,000$10,234$0$0$No1,750,000$Lien
Gabriel VilardiRochester (BUF)C/RW221999-08-16 22:26:45Yes215 Lbs6 ft3NoNoNoNo2Pro & Farm900,000$5,263$0$0$No900,000$
Ilya LyubushkinRochester (BUF)D281994-04-06 07:38:48No201 Lbs6 ft2NoNoNoNo1Pro & Farm975,000$5,702$0$0$NoLien
Josh NorrisRochester (BUF)C231999-05-05No194 Lbs6 ft2NoYesNoNo1Pro & Farm900,000$5,263$0$0$NoLien
Julian MelchioriRochester (BUF)D301991-12-06No220 Lbs6 ft5NoNoNoNo2Pro & Farm825,000$4,825$0$0$No825,000$Lien
Kevin Hayes (contrat à 1 volet)Rochester (BUF)C/LW301992-05-08No220 Lbs6 ft5NoYesYesYes1Pro & Farm2,500,000$25,000$0$NoLien
Lucas RaymondRochester (BUF)RW202002-03-28 08:47:47No182 Lbs5 ft11NoNoNoNo2Pro & Farm900,000$5,263$0$0$No900,000$Lien
Marcus KrugerRochester (BUF)C/LW/RW321990-05-27No187 Lbs6 ft0NoNoNoNo3Pro & Farm750,000$4,386$0$0$No750,000$750,000$Lien
Martin MarincinRochester (BUF)D301992-02-18No218 Lbs6 ft5NoNoNoNo2Pro & Farm1,100,000$6,433$0$0$No1,100,000$Lien
Nick MerkleyRochester (BUF)C/RW251997-05-23No198 Lbs5 ft10NoNoNoNo1Pro & Farm1,100,000$6,433$0$0$NoLien
Owen PowerRochester (BUF)D192002-11-22 03:52:12Yes218 Lbs6 ft6NoNoNoNo3Pro & Farm900,000$5,263$0$0$No900,000$900,000$
Scott DarlingRochester (BUF)G331988-12-22 06:40:45No241 Lbs6 ft6NoNoNoNo2Pro & Farm750,000$4,386$0$0$No750,000$Lien
Stuart SkinnerRochester (BUF)G231998-11-01 03:38:52Yes206 Lbs6 ft4NoNoNoNo2Pro & Farm500,000$2,924$0$0$No500,000$
Sven Baertschi (contrat à 1 volet)Rochester (BUF)LW/RW291992-10-05No200 Lbs5 ft11NoNoYesYes1Pro & Farm850,000$8,500$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1926.89205 Lbs6 ft21.68939,474$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Josh Norris35122
2Dominik KahunGabriel VilardiNick Merkley30122
3Sven BaertschiKevin HayesAndrew Shaw25122
4AJ GreerMarcus Kruger10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Owen PowerIlya Lyubushkin35122
2Martin MarincinDan Girardi30122
3Julian MelchioriBrendan Guhle25122
4Owen PowerIlya Lyubushkin10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Josh Norris50122
2Dominik KahunGabriel VilardiNick Merkley50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Owen PowerIlya Lyubushkin50122
2Martin MarincinDan Girardi50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Josh Norris50122
2Gabriel Vilardi50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Owen PowerIlya Lyubushkin50122
2Martin MarincinDan Girardi50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
150122Owen PowerIlya Lyubushkin50122
2Josh Norris50122Martin MarincinDan Girardi50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Josh Norris50122
2Gabriel Vilardi50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Owen PowerIlya Lyubushkin50122
2Martin MarincinDan Girardi50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Josh NorrisOwen PowerIlya Lyubushkin
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Josh NorrisOwen PowerIlya Lyubushkin
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Kevin Hayes, Sven Baertschi, AJ GreerKevin Hayes, Sven BaertschiAJ Greer
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Julian Melchiori, Brendan Guhle, Martin MarincinJulian MelchioriBrendan Guhle, Martin Marincin
Tirs de pénalité
, Josh Norris, , Gabriel Vilardi, Dominik Kahun
Gardien
#1 : Scott Darling, #2 :
Lignes d’attaque personnalisées en prolongation
, Josh Norris, , Gabriel Vilardi, Dominik Kahun, Kevin Hayes, Kevin Hayes, Nick Merkley, Sven Baertschi, AJ Greer, Andrew Shaw
Lignes de défense personnalisées en prolongation
Owen Power, Ilya Lyubushkin, Martin Marincin, Dan Girardi, Julian Melchiori


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
1Abbotsford21100000743110000005141010000023-120.500791600116989411981230117611136673218345120.00%40100.00%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
2Bakersfield2100010010100110000006511000010045-130.75010192900116989411981230117611136610225223510330.00%9455.56%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
3Bridgeport422000001413120200000811-32200000062440.500142438001169894111731230117611136618347467319526.32%23482.61%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
4Charlotte421000011819-12110000089-1210000011010050.625182846001169894111871230117611136619752359225832.00%10190.00%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
5Cleveland605010001627-11303000001016-630201000611-520.1671630460011698941123512301176111366264608313124729.17%37683.78%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
6Coachella Valley62201100242043100110014104312000001010070.5832445690111698941128012301176111366285764111234823.53%16381.25%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
7Eagles2010010058-31010000024-21000010034-110.2505914101169894117112301176111366952520458112.50%10280.00%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
8Grand Rapids6320100027261311010001314-1321000001412280.6672749760011698941126712301176111366253766211325624.00%29872.41%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
9Hartford631010102517842001010179821100000880100.8332541660011698941124312301176111366289786812127414.81%26484.62%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
10Hershey43100000191272200000012842110000074360.750193150001169894111921230117611136617751286416637.50%13653.85%11848366250.46%1927384850.08%741146950.44%1918129119736371083529
11Iowa220000001046110000007431100000030341.000101626011169894117612301176111366761412397228.57%6266.67%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
12Laval715000012136-1530300000915-6412000011221-930.21421365700116989411291123011761113663371027312030723.33%32584.38%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
13Lehigh Valley4110101013112211000006602000101075260.750132033001169894111581230117611136619145407115426.67%19384.21%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
14Manitoba20200000611-51010000048-41010000023-100.000612180011698941193123011761113669541163812216.67%8362.50%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
15Ontario31200000915-61010000034-121100000611-520.33391322001169894111161230117611136613538314713215.38%12558.33%21848366250.46%1927384850.08%741146950.44%1918129119736371083529
16Providence633000002322131200000912-3321000001410460.5002339620011698941124112301176111366284846311521419.05%28871.43%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
17Rockford220000001486110000008441100000064241.00014253900116989411931230117611136610127222510440.00%10280.00%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
18San Diego20200000612-61010000025-31010000047-300.000612180011698941196123011761113668219204710220.00%9544.44%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
19San Jose200001011214-21000000189-11000010045-120.5001223350011698941196123011761113661334624358450.00%11645.45%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
20Springfield21000100101001000010056-11100000054130.7501017270011698941193123011761113661313122314125.00%11190.91%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
21Syracuse211000007521010000013-21100000062420.500713200011698941110012301176111366802416341119.09%80100.00%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
22Texas2010100056-1100010004311010000013-220.50059140011698941192123011761113668617123914321.43%6183.33%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
23Wilkes-Barre/Scranton413000001519-42020000079-221100000810-220.250152944011169894111771230117611136617660397213323.08%16850.00%01848366250.46%1927384850.08%741146950.44%1918129119736371083529
Total82303606523316329-1341132004211168175-741171602312148154-6840.512316549865131169894113566123011761113663825105980315333618824.38%3538775.35%31848366250.46%1927384850.08%741146950.44%1918129119736371083529
_Since Last GM Reset82303606523316329-1341132004211168175-741171602312148154-6840.512316549865131169894113566123011761113663825105980315333618824.38%3538775.35%31848366250.46%1927384850.08%741146950.44%1918129119736371083529
_Vs Conference57212605122215222-72991503110113119-628121102012102103-1590.51821537258702116989411244412301176111366263673157810842496224.90%2495677.51%11848366250.46%1927384850.08%741146950.44%1918129119736371083529
_Vs Division259170310196108-121239021004053-1313680100156551260.520961652610011698941110861230117611136611513382494741122623.21%1072279.44%01848366250.46%1927384850.08%741146950.44%1918129119736371083529

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8284W1316549865356638251059803153313
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8230366523316329
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4113204211168175
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4117162312148154
Derniers 10 matchs
WLOTWOTL SOWSOL
730000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3618824.38%3538775.35%3
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
12301176111366116989411
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
1848366250.46%1927384850.08%741146950.44%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1918129119736371083529


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
313Hartford1Rochester2BWXXSommaire du match
528Laval5Rochester4BLSommaire du match
635Rochester3Grand Rapids5ALSommaire du match
846Rochester0Cleveland4ALSommaire du match
1058Hartford2Rochester5BWSommaire du match
1273Coachella Valley4Rochester5BWXSommaire du match
1375Rochester4Laval5ALXXSommaire du match
1590Rochester4Providence6ALSommaire du match
1799Rochester3Coachella Valley4ALSommaire du match
19114Cleveland5Rochester3BLSommaire du match
21124Rochester3Laval4ALSommaire du match
23136Providence3Rochester6BWSommaire du match
25150Cleveland6Rochester5BLSommaire du match
27166Rochester3Wilkes-Barre/Scranton10ALSommaire du match
29173Rochester4Laval1AWSommaire du match
31186Wilkes-Barre/Scranton5Rochester4BLSommaire du match
33199Hershey5Rochester6BWSommaire du match
35212Rochester1Hershey3ALSommaire du match
37223Charlotte7Rochester4BLSommaire du match
38235Rochester4San Jose5ALXSommaire du match
40249Cleveland5Rochester2BLSommaire du match
42256Rochester1Laval11ALSommaire du match
45274Coachella Valley0Rochester4BWSommaire du match
46279Rochester3Hartford6ALSommaire du match
49296Rochester3Bridgeport1AWSommaire du match
50304Rockford4Rochester8BWSommaire du match
53317Bridgeport4Rochester3BLSommaire du match
55330Rochester4Charlotte3AWSommaire du match
57340Rochester6Grand Rapids4AWSommaire du match
58350Providence6Rochester2BLSommaire du match
60361Rochester6Charlotte7ALXXSommaire du match
62375Rochester4San Diego7ALSommaire du match
63381Grand Rapids4Rochester5BWXSommaire du match
66397Bridgeport7Rochester5BLSommaire du match
68407Rochester2Abbotsford3ALSommaire du match
70419Iowa4Rochester7BWSommaire du match
71431Rochester3Eagles4ALXSommaire du match
73443Rochester5Wilkes-Barre/Scranton0AWSommaire du match
75454Providence3Rochester1BLSommaire du match
77465Rochester2Coachella Valley4ALSommaire du match
78476Wilkes-Barre/Scranton4Rochester3BLSommaire du match
81489Rochester6Rockford4AWSommaire du match
82498San Jose9Rochester8BLXXSommaire du match
85514Rochester6Syracuse2AWSommaire du match
87524Rochester2Manitoba3ALSommaire du match
88529Laval5Rochester1BLSommaire du match
90544Eagles4Rochester2BLSommaire du match
93562Rochester5Coachella Valley2AWSommaire du match
95571Springfield6Rochester5BLXSommaire du match
98588Laval5Rochester4BLSommaire du match
101604Rochester3Lehigh Valley2AWXSommaire du match
102612Rochester3Iowa0AWSommaire du match
104622San Diego5Rochester2BLSommaire du match
105636Rochester1Texas3ALSommaire du match
107644Texas3Rochester4BWXSommaire du match
109662Manitoba8Rochester4BLSommaire du match
110669Rochester4Bakersfield5ALXSommaire du match
112678Rochester6Hershey1AWSommaire du match
115690Charlotte2Rochester4BWSommaire du match
117700Rochester5Springfield4AWSommaire du match
119715Bakersfield5Rochester6BWSommaire du match
120728Rochester2Ontario9ALSommaire du match
122738Hartford2Rochester5BWSommaire du match
124749Rochester5Grand Rapids3AWSommaire du match
127761Coachella Valley6Rochester5BLXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
129773Rochester5Hartford2AWSommaire du match
132785Syracuse3Rochester1BLSommaire du match
134797Rochester4Lehigh Valley3AWXXSommaire du match
136804Rochester3Bridgeport1AWSommaire du match
138815Hartford4Rochester5BWXSommaire du match
140827Rochester4Ontario2AWSommaire du match
142837Ontario4Rochester3BLSommaire du match
146859Hershey3Rochester6BWSommaire du match
149879Grand Rapids3Rochester5BWSommaire du match
151895Lehigh Valley4Rochester3BLSommaire du match
156917Abbotsford1Rochester5BWSommaire du match
158934Rochester4Providence1AWSommaire du match
160940Lehigh Valley2Rochester3BWSommaire du match
163956Rochester6Providence3AWSommaire du match
164960Rochester4Cleveland6ALSommaire du match
167966Grand Rapids7Rochester3BLSommaire du match
168972Rochester2Cleveland1AWXSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance78,45239,290
Assistance PCT95.67%95.83%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2872 - 95.73% 148,585$6,091,998$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,870,610$ 1,450,000$ 1,450,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,480$ 1,373,530$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 11,404$ 11,404$




Rochester 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
1Max Willman21682112194-617635241779210.35%28395918.331547621701012013647.28%00.9805
2Dominik Kahun177661111773024982908088.17%43403122.78173350169000156447.71%10.8848
3Josh Norris133741021763510634634665711.26%45314323.63202646117606199452.99%21.1229
4Tobias Rieder1277090160144212621263111.09%61289022.7626255116600099343.19%31.1106
5Martin Frk2265179130-4661771856038.46%21334214.7911203110200025850.34%00.7824

Rochester 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
1Scott Darling934039110.9123.8853714234739250320.61526
2Stuart Skinner80383480.9213.5047618427835360800.83312
3Brian Elliott58331770.9093.0333674417018580210.53813
4Chris Driedger186620.9104.2191300647140200.60010

Rochester 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
2082352906705272282-1041161503205142151-941191403500130131-1942724767481497878210265789486786256278483276314933206119.06%3266280.98%11475300249.13%1485312547.52%673139548.24%1927131119566311080533
2182303606523316329-1341132004211168175-741171602312148154-684316549865131169894113566123011761113663825105980315333618824.38%3538775.35%31848366250.46%1927384850.08%741146950.44%1918129119736371083529
2182303606523316329-1341132004211168175-741171602312148154-684316549865131169894113566123011761113663825105980315333618824.38%3538775.35%31848366250.46%1927384850.08%741146950.44%1918129119736371083529
Total Saison régulière2469510101817411904940-361234255011627478501-231235346071124426439-132629041574247831032928327032978933543219308818810434295023694559104223722.74%103223677.13%751711032650.08%53391082149.34%2155433349.73%576338955902190732471592
Séries éliminatoires
20734000002528-3422000001818031200000710-36254469108412122571727210265746013338718.42%291065.52%011826544.53%12928245.74%5411646.55%163109182559246
Total Séries éliminatoires734000002528-3422000001818031200000710-36254469108412122571727210265746013338718.42%291065.52%011826544.53%12928245.74%5411646.55%163109182559246

Rochester 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
1Max Willman6751221012122626.92%113322.29325900001048.78%01.7900
2Jake Muzzin7178161213175.88%1317324.79134120000000%00.9200
3Dan Girardi6336601141520.00%1015425.7912370000100%00.7800
4Lucas Lessio714530211147.14%011616.69011300000036.36%00.8600
5Martin Frk741524372317.39%110915.70101600000166.67%00.9100

Rochester 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
1Brian Elliott73210.8943.83407202624501000
2Scott Darling10100.9471.94310011900100