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Connexion

Rochester
GP: 68 | W: 32 | L: 29 | OTL: 7 | P: 71
GF: 212 | GA: 211 | PP%: 14.62% | PK%: 80.34%
DG: JP Desmarais | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #895 vs Wilkes-Barre/Scranton

Centre de jeu
Hartford
33-33-5, 71pts
5
3 Rochester
32-29-7, 71pts
Team Stats
L1SéquenceW1
16-18-1Fiche domicile18-15-3
17-15-4Fiche domicile14-14-4
3-7-0Derniers 10 matchs4-6-0
3.24Buts par match 3.12
3.39Buts contre par match 3.10
22.93%Pourcentage en avantage numérique14.62%
79.77%Pourcentage en désavantage numérique80.34%
Utica
11-54-6, 28pts
1
7 Rochester
32-29-7, 71pts
Team Stats
L27SéquenceW1
6-26-3Fiche domicile18-15-3
5-28-3Fiche domicile14-14-4
0-10-0Derniers 10 matchs4-6-0
2.21Buts par match 3.12
5.17Buts contre par match 3.10
16.73%Pourcentage en avantage numérique14.62%
70.54%Pourcentage en désavantage numérique80.34%
Rochester
32-29-7, 71pts
Jour 165
Wilkes-Barre/Scranton
41-28-4, 86pts
Statistiques d’équipe
W1SéquenceL1
18-15-3Fiche domicile20-14-1
14-14-4Fiche visiteur21-14-3
4-6-010 derniers matchs5-3-2
3.12Buts par match 3.42
3.10Buts contre par match 3.42
14.62%Pourcentage en avantage numérique19.24%
80.34%Pourcentage en désavantage numérique79.62%
Hartford
33-33-5, 71pts
Jour 167
Rochester
32-29-7, 71pts
Statistiques d’équipe
L1SéquenceW1
16-18-1Fiche domicile18-15-3
17-15-4Fiche visiteur14-14-4
3-7-010 derniers matchs4-6-0
3.24Buts par match 3.12
3.39Buts contre par match 3.12
22.93%Pourcentage en avantage numérique14.62%
79.77%Pourcentage en désavantage numérique80.34%
Rochester
32-29-7, 71pts
Jour 170
Bridgeport
32-33-5, 69pts
Statistiques d’équipe
W1SéquenceL2
18-15-3Fiche domicile13-20-2
14-14-4Fiche visiteur19-13-3
4-6-010 derniers matchs4-5-1
3.12Buts par match 3.46
3.10Buts contre par match 3.46
14.62%Pourcentage en avantage numérique21.43%
80.34%Pourcentage en désavantage numérique82.28%
Meneurs d'équipe
Buts
Tobias Rieder
33
Calen AddisonPasses
Calen Addison
47
Points
Tobias Rieder
58
Plus/Moins
Brandon Sutter
18
Victoires
Thomas Greiss
17
Pourcentage d’arrêts
Thomas Greiss
0.918

Statistiques d’équipe
Buts pour
212
3.12 GFG
Tirs pour
2300
33.82 Avg
Pourcentage en avantage numérique
14.6%
37 GF
Début de zone offensive
39.7%
Buts contre
211
3.10 GAA
Tirs contre
2494
36.68 Avg
Pourcentage en désavantage numérique
80.3%%
58 GA
Début de la zone défensive
43.4%
Informations de l'équipe

Directeur généralJP Desmarais
EntraîneurCory Clouston
DivisionNord
ConférenceConference est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,207
Billets de saison300


Informations de la formation

Équipe Pro22
Équipe Mineure18
Limite contact 40 / 50
Espoirs38


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
1Zack KassianX100.00754770658970846569676562747672155000332950,000$
2Miikka SalomakiXX100.00663086727370926372626360765752345000313775,000$
3Brandon SutterXX100.006829926576699471827472687677732450003511,720,000$
4David KrejciX100.006529904271759672526571697298771450003811,100,000$
5Justin AbdelkaderXXX100.006937764773628462556466678298821450003721,500,000$
6Martin FrkXX100.00643288767474926773646853825850375000303800,000$
7Lucas LessioXX98.00683183658672896369626361695756275000313775,000$
8Sven BaertschiXX100.006430918181838973737169618064544350003131,250,000$
9Tobias RiederXX100.006830877672879374747273707965573950003111,100,000$
10Max WillmanXX100.00723079728478866667656962756154465000293975,000$
11AJ GreerX100.00795967739273956470636662755554485000251900,000$
12Dustin ByfuglienX100.00733955388671965250465288649486135000391875,000$
13Ilya LyubushkinX99.008433597488818854505552957664614050003021,300,000$
14Calen Addison (R)X100.00732787897885995872605282774743735000241800,000$
15Oliver KylingtonX99.007131929480899954735549867753497250002732,200,000$
16Adam Ginning (R)X100.00705599668275994150414287704645485800242600,000$
17Albert Johansson (R)X100.00783090707679994750475088704342725000242500,000$
Rayé
1Kevin HayesXX98.007440857592839774817072678270624750003221,800,000$
2Derek MeechX100.00572586357458884527403980728268135000401750,000$
3Brendan GuhleX100.00693185869180724470414778775646435000264775,000$
MOYENNE D’ÉQUIPE99.7070358268817692606459607275665938500
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
1Chris Driedger100.0064798180778487848580806261475000302925,000$
2Thomas Greiss100.00568182806886878888707495992350003821,300,000$
Rayé
MOYENNE D’ÉQUIPE100.006080828073858786877577798035500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Cory Clouston79878496909973CAN5521,800,000$


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
1Tobias RiederRochester (BUF)LW/RW67332558936086913037518510.89%19141421.111071750212000172374251.00%24900010.8214000634
2Calen AddisonRochester (BUF)D661047579340429212551838.00%115142521.6031013652150002236100%000100.8000000222
3Sven BaertschiRochester (BUF)LW/RW6816375342404189238761906.72%10144121.2028104821600042273152.00%17500000.7413000342
4Brandon SutterRochester (BUF)C/RW66192948182404987195491519.74%12134120.3327945208101102103352.03%66500010.7204000331
5David KrejciRochester (BUF)C6822254741204598184489511.96%15121917.935510472150001224240.23%164800010.7700000324
6Kevin HayesRochester (BUF)C/LW5013284114521089103183531197.10%11121724.351673115300061692153.91%179200000.6703001323
7Zack KassianRochester (BUF)RW6817223908925173321673613410.18%8118017.36461034212000002042.31%10400000.6600113231
8Ilya LyubushkinRochester (BUF)D607313888001336811839865.93%136147824.63459561900000181200%000000.5100000023
9Max WillmanRochester (BUF)C/LW68112132830054107142441097.75%1394713.94022426000051049.03%97700000.6801000112
10Albert JohanssonRochester (BUF)D6581927-9300665810027608.00%121134520.69235401940003218200%000000.4000000150
11Martin FrkRochester (BUF)LW/RW68121325101602959125351169.60%587412.8600000000083050.00%6200000.5700000001
12Dustin ByfuglienRochester (BUF)D68913229640793272245312.50%106136420.07426271930111212100%000010.3200000110
13Adam GinningRochester (BUF)D686162294810525249243712.24%8299914.70000412000066100%000000.4400002002
14Justin AbdelkaderRochester (BUF)C/LW/RW687142112421060529925627.07%597714.37000130000601042.86%23800000.4300011000
15Brendan GuhleRochester (BUF)D666131910460845053114311.32%4893114.1100005000022000%000000.4100000112
16AJ GreerRochester (BUF)LW6797164335551768115013.24%14046.0400000000031137.93%2900000.7900100111
17Lucas LessioRochester (BUF)LW/RW6856112120192447173110.64%35488.0600000000000046.51%17200000.4000000000
18Miikka SalomakiRochester (BUF)LW/RW68044140813167160%32043.0000006000060043.18%13200000.3900000001
19Derek MeechRochester (BUF)D661234007566216.67%252964.4900001000019000%000000.2000000000
20Oliver KylingtonRochester (BUF)D2000-100019230%25025.350006700007000%00000000000000
Statistiques d’équipe totales ou en moyenne12552113725831256766011711130229966016259.18%7401966215.673761984582075112441915311048.01%624300140.59215227273029
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
1Thomas GreissRochester (BUF)48172360.9182.9928126014017100020.750124621442
2Chris DriedgerRochester (BUF)2215610.9163.05130021667820000.66732245141
Statistiques d’équipe totales ou en moyenne70322970.9173.014112812062492002156866583


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 ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer 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
AJ GreerRochester (BUF)LW251998-09-02CANNo208 Lbs6 ft3NoNoN/ANoNo12024-09-15FalseFalsePro & Farm900,000$152,308$0$0$No---------------------------
Adam GinningRochester (BUF)D242000-01-13SWEYes188 Lbs6 ft3NoNoProspectNoNo22025-10-30FalseFalsePro & Farm600,000$101,538$0$0$No600,000$--------600,000$--------No--------
Albert JohanssonRochester (BUF)D242000-01-04SWEYes168 Lbs6 ft0NoNoProspectNoNo22025-10-30FalseFalsePro & Farm500,000$84,615$0$0$No500,000$--------500,000$--------No--------
Brandon SutterRochester (BUF)C/RW351989-02-14USANo192 Lbs6 ft3NoNoTrade2025-03-13NoNo12024-09-25FalseFalsePro & Farm1,720,000$291,077$0$0$No---------------------------Lien
Brendan GuhleRochester (BUF)D261997-07-29CANNo197 Lbs6 ft2NoNoN/ANoNo42025-09-09FalseFalsePro & Farm775,000$131,154$0$0$No775,000$775,000$775,000$------775,000$775,000$775,000$------NoNoNo------Lien
Calen AddisonRochester (BUF)D242000-04-11CANYes173 Lbs5 ft11NoNoTrade2024-10-08NoNo1FalseFalsePro & Farm800,000$135,385$0$0$No---------------------------Lien NHL
Chris DriedgerRochester (BUF)G301994-05-18CANNo208 Lbs6 ft4NoNoN/ANoNo22025-09-09FalseFalsePro & Farm925,000$156,538$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
David KrejciRochester (BUF)C381986-04-28CZENo194 Lbs6 ft0NoNoFree AgentNoNo12024-10-07FalseFalsePro & Farm1,100,000$186,154$0$0$No---------------------------
Derek MeechRochester (BUF)D401984-04-21CANNo210 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm750,000$126,923$0$0$No---------------------------
Dustin ByfuglienRochester (BUF)D391985-03-27USANo263 Lbs6 ft5NoNoFree AgentNoNo12024-10-02FalseFalsePro & Farm875,000$148,077$0$0$No---------------------------Lien
Ilya LyubushkinRochester (BUF)D301994-04-06RUSNo201 Lbs6 ft2NoNoTrade2025-07-25NoNo22025-09-09FalseFalsePro & Farm1,300,000$220,000$0$0$No1,300,000$--------1,300,000$--------No--------Lien
Justin AbdelkaderRochester (BUF)C/LW/RW371987-02-25USANo212 Lbs6 ft1NoNoFree AgentNoNo22024-09-25FalseFalsePro & Farm1,500,000$253,846$0$0$No1,500,000$--------1,500,000$--------No--------
Kevin HayesRochester (BUF)C/LW321992-05-08USANo220 Lbs6 ft5NoNoFree AgentNoNo22024-09-28FalseFalsePro & Farm1,800,000$304,615$0$0$No1,800,000$--------1,800,000$--------No--------Lien / Lien NHL
Lucas LessioRochester (BUF)LW/RW311993-01-23CANNo217 Lbs6 ft1NoNoN/ANoNo32024-09-15FalseFalsePro & Farm775,000$131,154$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien
Martin FrkRochester (BUF)LW/RW301993-10-05CZENo212 Lbs6 ft1NoNoN/ANoNo32024-09-15FalseFalsePro & Farm800,000$135,385$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien
Max WillmanRochester (BUF)C/LW291995-02-13USANo198 Lbs6 ft1NoNoN/ANoNo32024-09-15FalseFalsePro & Farm975,000$165,000$0$0$No975,000$975,000$-------975,000$975,000$-------NoNo-------Lien NHL
Miikka SalomakiRochester (BUF)LW/RW311993-03-09FINNo211 Lbs5 ft11NoNoN/ANoNo32024-09-15FalseFalsePro & Farm775,000$131,154$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien
Oliver Kylington (contrat à 1 volet)Rochester (BUF)D271997-05-19SWENo183 Lbs6 ft0NoNoN/AYesYes32024-09-15FalseFalsePro & Farm2,200,000$418,000$22,000$4,180$No2,200,000$2,200,000$-------2,200,000$2,200,000$-------NoNo-------Lien NHL
Sven BaertschiRochester (BUF)LW/RW311992-10-05SWINo200 Lbs5 ft11NoNoN/ANoNo32024-09-15FalseFalsePro & Farm1,250,000$211,538$0$0$No1,250,000$1,250,000$-------1,250,000$1,250,000$-------NoNo-------Lien
Thomas GreissRochester (BUF)G381986-01-29GERNo221 Lbs6 ft0NoNoFree AgentNoNo22024-09-25FalseFalsePro & Farm1,300,000$220,000$0$0$No1,300,000$--------1,300,000$--------No--------
Tobias RiederRochester (BUF)LW/RW311993-01-10GERNo196 Lbs5 ft11NoNoN/ANoNo12024-09-15FalseFalsePro & Farm1,100,000$186,154$0$0$No---------------------------Lien
Zack KassianRochester (BUF)RW331991-01-24CANNo211 Lbs6 ft3NoNoFree AgentNoNo22024-09-25FalseFalsePro & Farm950,000$160,769$0$0$No950,000$--------950,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2231.14204 Lbs6 ft12.051,075,909$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tobias RiederJustin Abdelkader35122
2Sven BaertschiDavid KrejciZack Kassian30122
3AJ GreerBrandon SutterLucas Lessio25122
4Martin FrkMiikka Salomaki10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinOliver Kylington35122
2Calen AddisonDustin Byfuglien30122
3Albert JohanssonAdam Ginning25122
4Ilya LyubushkinOliver Kylington10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tobias RiederBrandon Sutter50122
2Sven BaertschiDavid KrejciZack Kassian50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinOliver Kylington50122
2Calen AddisonDustin Byfuglien50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Brandon Sutter50122
2Tobias RiederSven Baertschi50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinOliver Kylington50122
2Calen AddisonDustin Byfuglien50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
150122Ilya LyubushkinOliver Kylington50122
2Brandon Sutter50122Calen AddisonDustin Byfuglien50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Brandon Sutter50122
2Tobias RiederSven Baertschi50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinOliver Kylington50122
2Calen AddisonDustin Byfuglien50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tobias RiederBrandon SutterIlya LyubushkinOliver Kylington
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tobias RiederBrandon SutterIlya LyubushkinOliver Kylington
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Miikka Salomaki, Max Willman, AJ GreerMiikka Salomaki, Max WillmanAJ Greer
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Albert Johansson, Adam Ginning, Calen AddisonAlbert JohanssonAdam Ginning, Calen Addison
Tirs de pénalité
, Brandon Sutter, Tobias Rieder, Sven Baertschi, David Krejci
Gardien
#1 : Thomas Greiss, #2 : Chris Driedger
Lignes d’attaque personnalisées en prolongation
, Brandon Sutter, Tobias Rieder, Sven Baertschi, David Krejci, Max Willman, Zack Kassian, AJ Greer, Justin Abdelkader, Martin Frk
Lignes de défense personnalisées en prolongation
Ilya Lyubushkin, Oliver Kylington, Calen Addison, Dustin Byfuglien, Albert Johansson


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
1Abbotsford21100000651110000004221010000023-120.50061016007675557517787577295174252127300.00%80100.00%01193252647.23%1300275947.12%524107248.88%156910431647528900443
2Bakersfield20101000810-21010000036-31000100054120.500813210076755577077875772951711322349222.22%11463.64%01193252647.23%1300275947.12%524107248.88%156910431647528900443
3Charlotte504000101019-92010001056-130300000513-820.200101525007675557144778757729511876444811915.26%22577.27%01193252647.23%1300275947.12%524107248.88%156910431647528900443
4Cleveland3110010067-13110010067-10000000000030.5006111700767555790778757729511122339421317.69%16287.50%01193252647.23%1300275947.12%524107248.88%156910431647528900443
5Coachella Valley2020000014-31010000001-11010000013-200.000112007675557407787577295171302442500.00%12375.00%01193252647.23%1300275947.12%524107248.88%156910431647528900443
6Eagles311010001091210010008621010000023-140.667101727007675557987787577295111238285310330.00%13376.92%01193252647.23%1300275947.12%524107248.88%156910431647528900443
7Grand Rapids4130000015150211000009722020000068-220.2501526410076755571347787577295112935336815213.33%14564.29%01193252647.23%1300275947.12%524107248.88%156910431647528900443
8Hartford3120000079-21010000035-22110000044020.333713201176755571007787577295110232375614214.29%15473.33%01193252647.23%1300275947.12%524107248.88%156910431647528900443
9Hershey4400000015872200000010552200000053281.0001525400076755571167787577295113341377218422.22%14192.86%01193252647.23%1300275947.12%524107248.88%156910431647528900443
10Iowa22000000853110000003121100000054141.00081321007675557927787577295169201032700.00%50100.00%01193252647.23%1300275947.12%524107248.88%156910431647528900443
11Laval614000011624-831200000910-130200001714-730.2501627431076755571927787577295120580571102114.76%22672.73%01193252647.23%1300275947.12%524107248.88%156910431647528900443
12Lehigh Valley21000001550000000000002100000155030.7505914007675557597787577295170262341700.00%8187.50%01193252647.23%1300275947.12%524107248.88%156910431647528900443
13Manitoba30101100811-31010000014-32000110077030.50081624007675557131778757729511102826501317.69%10460.00%01193252647.23%1300275947.12%524107248.88%156910431647528900443
14Ontario22000000844110000005321100000031241.000815230076755575577875772951702126399222.22%13192.31%01193252647.23%1300275947.12%524107248.88%156910431647528900443
15Providence31101000111102110000078-11000100043140.66711182900767555792778757729511352320558450.00%10190.00%01193252647.23%1300275947.12%524107248.88%156910431647528900443
16Rockford2010010047-31010000024-21000010023-110.250461000767555761778757729519520182413215.38%7271.43%01193252647.23%1300275947.12%524107248.88%156910431647528900443
17San Diego32100000981321000009810000000000040.6679162500767555789778757729511092946499222.22%19573.68%11193252647.23%1300275947.12%524107248.88%156910431647528900443
18San Jose211000007431010000023-11100000051420.500713200076755576077875772951902223336116.67%90100.00%01193252647.23%1300275947.12%524107248.88%156910431647528900443
19Springfield211000006601010000012-11100000054120.50061117007675557707787577295174222843600.00%13284.62%01193252647.23%1300275947.12%524107248.88%156910431647528900443
20Syracuse41101100181442000110077021100000117450.6251835530076755571937787577295116347427813323.08%21576.19%01193252647.23%1300275947.12%524107248.88%156910431647528900443
21Texas2110000067-1110000004311010000024-220.50061016007675557777787577295167228328112.50%40100.00%01193252647.23%1300275947.12%524107248.88%156910431647528900443
22Utica 440000002291322000000112922000000117481.0002241630076755571767787577295113338346012433.33%17288.24%01193252647.23%1300275947.12%524107248.88%156910431647528900443
23Wilkes-Barre/Scranton30200001610-42010000146-21010000024-210.16761117007675557110778757729511134138521516.67%12283.33%01193252647.23%1300275947.12%524107248.88%156910431647528900443
Total6826290541321221113615150221111310673211140320299105-6710.522212372584217675557230077875772951249474068411732533714.62%2955880.34%11193252647.23%1300275947.12%524107248.88%156910431647528900443
_Since Last GM Reset6826290541321221113615150221111310673211140320299105-6710.522212372584217675557230077875772951249474068411732533714.62%2955880.34%11193252647.23%1300275947.12%524107248.88%156910431647528900443
_Vs Conference4115180221313113102188012117163820710010026068-8410.50013123136221767555714067787577295114824504047151552314.84%1713480.12%01193252647.23%1300275947.12%524107248.88%156910431647528900443
_Vs Division22413021117083-131135011103738-11118010013345-12160.3647012119110767555775577875772951819249196392761114.47%892275.28%01193252647.23%1300275947.12%524107248.88%156910431647528900443

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6871W121237258423002494740684117321
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6826295413212211
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3615152211113106
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
321114320299105
Derniers 10 matchs
WLOTWOTL SOWSOL
460000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2533714.62%2955880.34%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
778757729517675557
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
1193252647.23%1300275947.12%524107248.88%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
156910431647528900443


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
12Rochester1Laval4LSommaire du match
419San Diego3Rochester4WSommaire du match
939Cleveland3Rochester2LXSommaire du match
1352Laval2Rochester5WSommaire du match
1460Rochester0Charlotte3LSommaire du match
1879Hershey1Rochester4WSommaire du match
22101Charlotte3Rochester4WXXSommaire du match
25112Rochester2Wilkes-Barre/Scranton4LSommaire du match
27127Eagles3Rochester4WXSommaire du match
32151Cleveland3Rochester4WSommaire du match
35169Rochester3Lehigh Valley2WSommaire du match
36175San Diego2Rochester3WSommaire du match
38189Rochester3Charlotte7LSommaire du match
40200Grand Rapids5Rochester3LSommaire du match
43215Rochester4Grand Rapids5LSommaire du match
45222Rochester5Bakersfield4WXSommaire du match
46227Cleveland1Rochester0LSommaire du match
50250Iowa1Rochester3WSommaire du match
53262Rochester2Hershey1WSommaire du match
56276Ontario3Rochester5WSommaire du match
58288Rochester5San Jose1WSommaire du match
61301Rochester4Utica 3WSommaire du match
62306Syracuse3Rochester4WXSommaire du match
65326Wilkes-Barre/Scranton2Rochester1LSommaire du match
67335Rochester1Coachella Valley3LSommaire du match
69346Rochester2Rockford3LXSommaire du match
71352Bakersfield6Rochester3LSommaire du match
72363Rochester5Iowa4WSommaire du match
75377Hershey4Rochester6WSommaire du match
77393Rochester3Manitoba4LXSommaire du match
79403Rockford4Rochester2LSommaire du match
81418Rochester2Texas4LSommaire du match
82426Wilkes-Barre/Scranton4Rochester3LXXSommaire du match
84438Rochester4Manitoba3WXSommaire du match
86452Rochester3Hershey2WSommaire du match
88460Springfield2Rochester1LSommaire du match
91476Rochester2Lehigh Valley3LXXSommaire du match
93482Rochester9Syracuse3WSommaire du match
94489San Diego3Rochester2LSommaire du match
97506Coachella Valley1Rochester0LSommaire du match
102529Manitoba4Rochester1LSommaire du match
104544Rochester4Laval5LXXSommaire du match
106554Charlotte3Rochester1LSommaire du match
109577Syracuse4Rochester3LXSommaire du match
111585Rochester7Utica 4WSommaire du match
112596Abbotsford2Rochester4WSommaire du match
114608Rochester5Springfield4WSommaire du match
116616Rochester2Laval5LSommaire du match
118628Eagles3Rochester4WSommaire du match
122647Rochester2Charlotte3LSommaire du match
123654Texas3Rochester4WSommaire du match
127677Grand Rapids2Rochester6WSommaire du match
128685Rochester2Eagles3LSommaire du match
132701Providence4Rochester2LSommaire du match
133709Rochester2Syracuse4LSommaire du match
136726Providence4Rochester5WSommaire du match
137735Rochester4Providence3WXSommaire du match
139749San Jose3Rochester2LSommaire du match
142765Rochester2Abbotsford3LSommaire du match
143770Rochester2Grand Rapids3LSommaire du match
144780Laval5Rochester3LSommaire du match
149803Laval3Rochester1LSommaire du match
150806Rochester3Ontario1WSommaire du match
152818Rochester2Hartford0WSommaire du match
154829Utica 1Rochester4WSommaire du match
156843Rochester2Hartford4LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
158852Hartford5Rochester3LSommaire du match
162877Utica 1Rochester7WSommaire du match
165895Rochester-Wilkes-Barre/Scranton-
167902Hartford-Rochester-
170915Rochester-Bridgeport-
171924Rochester-San Diego-
173929Bridgeport-Rochester-
175940Rochester-Bridgeport-
178953Rochester-Cleveland-
179957Rochester-Providence-
180963Bridgeport-Rochester-
182973Rochester-San Diego-
184978Rochester-Cleveland-
187989Lehigh Valley-Rochester-
188999Rochester-Wilkes-Barre/Scranton-
1941022Lehigh Valley-Rochester-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance53,61225,834
Assistance PCT74.46%71.76%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
5 2207 - 73.56% 129,586$4,665,087$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,274,134$ 2,147,000$ 2,147,000$ 1,800,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
11,010$ 1,778,714$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
647,929$ 33 20,241$ 667,953$




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

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

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

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

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