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Pittsburgh Penguins
GP: 34 | W: 18 | L: 15 | OTL: 1 | P: 50
GF: 97 | GA: 93 | PP%: 14.29% | PK%: 79.56%
DG: Jeff | Morale : 40 | Moyenne d’équipe : 76
Prochains matchs #479 vs New York Rangers

Centre de jeu
Pittsburgh Penguins
18-15-1, 50pts
2
3 Detroit Red Wings
17-9-7, 55pts
Team Stats
L2SéquenceW1
8-9-0Fiche domicile8-4-4
10-6-1Fiche visiteur9-5-3
5-4-1Derniers 10 matchs5-2-3
2.85Buts par match 2.73
2.74Buts contre par match 2.61
14.29%Pourcentage en avantage numérique18.60%
79.56%Pourcentage en désavantage numérique81.08%
New York Islanders
18-15-1, 51pts
3
1 Pittsburgh Penguins
18-15-1, 50pts
Team Stats
W2SéquenceL2
7-7-1Fiche domicile8-9-0
11-8-0Fiche visiteur10-6-1
7-3-0Derniers 10 matchs5-4-1
2.44Buts par match 2.85
2.50Buts contre par match 2.74
16.28%Pourcentage en avantage numérique14.29%
79.28%Pourcentage en désavantage numérique79.56%
New York Rangers
14-14-6, 46pts
Jour 85
Pittsburgh Penguins
18-15-1, 50pts
Statistiques d’équipe
W1SéquenceL2
5-9-3Fiche domicile8-9-0
9-5-3Fiche visiteur10-6-1
5-4-110 derniers matchs5-4-1
2.50Buts par match 2.85
2.74Buts contre par match 2.85
18.44%Pourcentage en avantage numérique14.29%
81.31%Pourcentage en désavantage numérique79.56%
Pittsburgh Penguins
18-15-1, 50pts
Jour 88
New Jersey Devils
18-9-7, 59pts
Statistiques d’équipe
L2SéquenceOTL1
8-9-0Fiche domicile8-6-5
10-6-1Fiche visiteur10-3-2
5-4-110 derniers matchs5-1-4
2.85Buts par match 2.76
2.74Buts contre par match 2.76
14.29%Pourcentage en avantage numérique16.28%
79.56%Pourcentage en désavantage numérique85.83%
Pittsburgh Penguins
18-15-1, 50pts
Jour 92
Anaheim Mighty Ducks
15-14-4, 43pts
Statistiques d’équipe
L2SéquenceL2
8-9-0Fiche domicile7-8-3
10-6-1Fiche visiteur8-6-1
5-4-110 derniers matchs3-5-2
2.85Buts par match 2.67
2.74Buts contre par match 2.67
14.29%Pourcentage en avantage numérique23.01%
79.56%Pourcentage en désavantage numérique78.82%
Meneurs d'équipe
Buts
Matt Boldy
17
Passes
Kasperi Kapanen
22
Points
Matt Boldy
33
Plus/Moins
Brandon Carlo
14
Victoires
Connor Hellebuyck
13
Pourcentage d’arrêts
Connor Hellebuyck
0.913

Statistiques d’équipe
Buts pour
97
2.85 GFG
Tirs pour
1027
30.21 Avg
Pourcentage en avantage numérique
14.3%
16 GF
Début de zone offensive
38.3%
Buts contre
93
2.74 GAA
Tirs contre
1036
30.47 Avg
Pourcentage en désavantage numérique
79.6%%
28 GA
Début de la zone défensive
37.8%
Informations de l'équipe

Directeur généralJeff
DivisionNortheast Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

NomPPG Paints Arena
Capacité18,000
Assistance14,401
Billets de saison7,740


Informations de la formation

Équipe Pro22
Équipe Mineure28
Limite contact 50 / 250
Espoirs62


Finance

Revenu annuel à ce jour17,755,506$
Dépenses annuelles à ce jour29,892,167$
Revenus de la saison estimés24,022,155$
Dépenses de la saison estimées38,317,020$
Compte bancaire actuel127,916,041$
Compte bancaire projeté113,882,718$


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
1Jack Hughes0X100.0058389196589399917591906692887440408102414,680,000$
2Jordan Kyrou0X100.0057458488758893896790907087747455408002717,500,000$
3Kasperi Kapanen0X100.0078448591708686837990907082777955408002817,500,000$
4Matt Boldy0X99.0063528584758995857085907285697855407902414,680,000$
5Seth Jarvis (R)0X100.0081428699539294787383857083677055407802324,680,000$
6Ryan Nugent-Hopkins0X100.0056439594679095819081817179807755407703213,600,000$
7Joel Eriksson Ek0X99.0089508476828990749280787573778455407602821,350,000$
8Nick Ritchie0X100.009264686293848473707771716778785540720292550,000$
9Rasmus Asplund0X100.006145848273818066676973737172745540700272500,000$
10Tom Kuhnhackl0X100.007643767472807569637369656981675540690331850,000$
11Dominic Toninato0X100.007847747276777964786765706680725540680312500,000$
12Tomas Nosek0X100.005947756481767860726664686278685540650322700,000$
13Josh Morrissey0X100.0093467885809898796984748873797455408203034,285,715$
14Brandon Carlo0X99.0091589077998994757483678466778955408002813,000,000$
15Martin Fehervary0X100.00995084838591997550777083697186554080N02513,480,000$
16Calen Addison0X100.005938859963829082538773727873755540760251700,000$
17Vladislav Gavrikov0X100.0073528773938586735075678266787555407502911,350,000$
18Jonas Siegenthaler0X100.0062558473958184705073668064778455407402811,200,000$
Rayé
1Jake Guentzel0X95.1892448396559092886986917289748055408103015,250,000$
2Juuso Valimaki0X100.005853817589798273507664766471705540720263500,000$
Équipe Mineure
1Kirill Marchenko (R)0X98.005942848475908280608285718170805540760243800,000$
2Marco Rossi (R)0X99.0061408389558989758280786478687855407402331,750,000$
3Ridly Greig (R)0X99.0088496689698593698073757775656855407402221,000,000$
4Bobby Brink (R)0X96.0058338493508383697373777176686955407202321,000,000$
5Matt Coronato (R)0X99.0055458388618880717072777077657555407202231,500,000$
6Axel Jonsson-Fjallby0X99.006944797573778563586665726776775540680271800,000$
7Dominik Simon0X100.007544757764757665676969676978665540680301560,000$
8Jiri Kulich (R)0X100.0056357889588080637768716472636355406802131,250,000$
9Greg McKegg0X100.006446756867777664796864636581725540660331500,000$
10Martin Frk0X100.005846756578756962556366656578705540650311700,000$
11Trey Fix-Wolansky0X100.005735807757707060526261736475695540650262600,000$
12Jack Studnicka0X100.007342797075728060695661676375685540640262700,000$
13Joe Morrow0X99.006747867190808272507366766380835540730321950,000$
14Kris Letang0X100.008150676690818263506759725788865540720381650,000$
15Nick DeSimone0X100.006044817477717970507264746279795540700303800,000$
16NICLAS ALMARI0X99.005545827876606065487363846272825240700271250,000$
17Paul LaDue0X100.007148786883717166506762666079725540670321650,000$
18Juuso Riikola0X100.008840827450697162506461675878675540660312500,000$
19Oskar Sundqvist0X89.167050766879727263756764656577705540660312500,000$
20Dennis Rasmussen0X100.006047816477738161776463656281765540650341750,000$
21Kyle Criscuolo0X100.006035757750687757616661686379605540640331675,000$
22EETU PELTOLA0X100.005648746986606062486963745969695240660251275,000$
23Jack Rathbone0X100.005435818458687661506161646273705540650261600,000$
24Ethan Prow0X100.005140847560657360505662655978725540640321650,000$
25Ashton Sautner0X100.006715827655686760506059645865607540630311650,000$
MOYENNE D’ÉQUIPE99.32694481797280827064737171697574554072
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
1Connor Hellebuyck099.007487878683858684848584816855408103237,000,000$
2Petr Mrazek099.008282858284848584878483826855408003323,600,000$
Rayé
Équipe Mineure
1Reto Berra097.007065708677818178778179897055407603811,050,000$
2STEFANOS LEKKAS099.00796060747877787878777874625240720291275,000$
3TIM JUEL0100.00526060747979808080797975645240720301350,000$
MOYENNE D’ÉQUIPE98.8071717280808182818181818066544076
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Matt BoldyPittsburgh PenguinsLW341716331041252659134458412.69%1467319.8111278003381171048.65%372816000.9800302322
2Jake GuentzelPittsburgh PenguinsLW3381826219564428124539.88%1356817.22371017950003380035.14%372310000.9100100301
3Kasperi KapanenPittsburgh PenguinsC3442226-2281041467621345.26%1155716.3919101397000172147.96%538179000.9300002100
4Jack HughesPittsburgh PenguinsLW3481523-32023319435778.51%855216.244481298000012047.62%21169000.8300000102
5Josh MorrisseyPittsburgh PenguinsD34813211183151026370172611.43%3885425.14325151101234103120%01138000.4900201222
6Joel Eriksson EkPittsburgh PenguinsC348122074420697368264611.76%1666819.6602228011241203052.79%771713000.6000022021
7Ryan Nugent-HopkinsPittsburgh PenguinsC3471118300225965233710.77%1663818.7830391110229582052.82%4431110100.5600000230
8Jordan KyrouPittsburgh PenguinsRW3498171140373783174110.84%954416.00022581000001138.46%131814000.6200000121
9Seth JarvisPittsburgh PenguinsRW349514-3180394259202915.25%1253315.70000170000003050.00%24127000.5200000012
10Brandon CarloPittsburgh PenguinsD341101114241049733821142.63%3974922.03000030002133000%0239100.2901002111
11Rasmus AsplundPittsburgh PenguinsRW344711417521274111279.76%1146313.6200002000001052.17%2359000.4700010001
12Calen AddisonPittsburgh PenguinsD342810-12020333214206.25%3153415.7310137200008000%02116000.3700000020
13Martin FehervaryPittsburgh PenguinsD34178220078443815152.63%4063818.7700004000074000%01019000.2500000000
14Tom KuhnhacklPittsburgh PenguinsLW344483315211340142910.00%32677.85000041013610100.00%125000.6000001100
15Nick RitchiePittsburgh PenguinsRW3452764515592038122213.16%934410.120000142024540164.29%1437000.4100102111
16Vladislav GavrikovPittsburgh PenguinsD3404471551747321070%3662018.2600000000177000%0514000.1300001000
17Dominic ToninatoPittsburgh PenguinsC3412372752022154176.67%72908.56000020001310044.33%9733000.2100001000
18Jonas SiegenthalerPittsburgh PenguinsD34123-260154223384.35%2648814.3600000011241100%0621000.1200000001
19Tomas NosekPittsburgh PenguinsC1000100100000%066.370000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne612971662636743612072477310273325869.44%339999316.331627438493459144287518550.62%2019200259200.53017314161615
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
1Connor HellebuyckPittsburgh Penguins2013700.9132.641205405361227520002014211
2Petr MrazekPittsburgh Penguins145810.9062.86840204042421300001420120
Statistiques d’équipe totales ou en moyenne34181510.9102.732045609310364882003434331


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
Brandon Carlo (contrat à 1 volet)Pittsburgh PenguinsD281996-11-26USANo216 Lbs6 ft5NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm3,000,000$1,675,532$0$0$No---------------------------Lien
Calen AddisonPittsburgh PenguinsD252000-04-11CANNo172 Lbs5 ft11NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm700,000$390,957$0$0$No---------------------------Lien
Connor Hellebuyck (contrat à 1 volet)Pittsburgh PenguinsG321993-05-19USANo207 Lbs6 ft4NoNoFree AgentNoNo32025-10-03FalseFalsePro & Farm7,000,000$3,909,574$0$0$No7,000,000$7,000,000$-------7,000,000$7,000,000$-------NoNo-------Lien
Dominic ToninatoPittsburgh PenguinsC311994-03-09USANo201 Lbs6 ft2NoNoAssign ManuallyNoNo22025-09-30FalseFalsePro & Farm500,000$279,255$0$0$No500,000$--------500,000$--------No--------Lien
Jack Hughes (contrat à 1 volet)Pittsburgh PenguinsLW242001-05-14USANo176 Lbs5 ft11NoNoProspectNoNo12025-09-30FalseFalsePro & Farm4,680,000$2,613,830$0$0$No---------------------------Lien / Lien NHL
Jake Guentzel (contrat à 1 volet)Pittsburgh PenguinsLW301994-10-06USANo181 Lbs5 ft11NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm5,250,000$2,932,181$0$0$No---------------------------Lien
Joel Eriksson EkPittsburgh PenguinsC281997-01-29SWENo207 Lbs6 ft2NoNoAssign ManuallyNoNo22025-09-30FalseFalsePro & Farm1,350,000$753,989$0$0$No1,350,000$--------1,350,000$--------No--------Lien
Jonas SiegenthalerPittsburgh PenguinsD281997-05-06CHENo218 Lbs6 ft2NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm1,200,000$670,213$0$0$No---------------------------Lien
Jordan Kyrou (contrat à 1 volet)Pittsburgh PenguinsRW271998-05-05CANNo174 Lbs6 ft0NoNoFree AgentNoNo12025-10-13FalseFalsePro & Farm7,500,000$4,188,830$0$0$No---------------------------Lien
Josh Morrissey (contrat à 1 volet)Pittsburgh PenguinsD301995-03-28CANNo194 Lbs6 ft0NoNoAssign ManuallyNoNo32025-09-30FalseFalsePro & Farm4,285,715$2,393,617$0$0$No4,285,715$4,285,715$-------4,285,715$4,285,715$-------NoNo-------Lien
Juuso ValimakiPittsburgh PenguinsD261998-10-06FINNo212 Lbs6 ft2NoNoAssign ManuallyNoNo32025-09-30FalseFalsePro & Farm500,000$279,255$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien
Kasperi Kapanen (contrat à 1 volet)Pittsburgh PenguinsC281996-07-23FINNo194 Lbs6 ft1NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm7,500,000$4,188,830$0$0$No---------------------------Lien
Martin Fehervary (contrat à 1 volet)Pittsburgh PenguinsD251999-10-06SVKNo203 Lbs6 ft2YesNoFree AgentNoNo12025-10-19FalseFalsePro Only3,480,000$1,943,617$0$0$No---------------------------Lien
Matt Boldy (contrat à 1 volet)Pittsburgh PenguinsLW242001-04-05USANo201 Lbs6 ft2NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm4,680,000$2,613,830$0$0$No---------------------------Lien
Nick RitchiePittsburgh PenguinsRW291995-12-05CANNo236 Lbs6 ft3NoNoFree AgentNoNo22025-11-01FalseFalsePro & Farm550,000$307,181$0$0$No550,000$--------550,000$--------No--------
Petr Mrazek (contrat à 1 volet)Pittsburgh PenguinsG331992-02-14CZENo187 Lbs6 ft2NoNoFree AgentNoNo22025-10-03FalseFalsePro & Farm3,600,000$2,010,638$0$0$No3,600,000$--------3,600,000$--------No--------Lien
Rasmus AsplundPittsburgh PenguinsRW271997-12-03SWENo185 Lbs5 ft11NoNoAssign ManuallyNoNo22025-09-30FalseFalsePro & Farm500,000$279,255$0$0$No500,000$--------500,000$--------No--------Lien
Ryan Nugent-Hopkins (contrat à 1 volet)Pittsburgh PenguinsC321993-04-12CANNo194 Lbs6 ft0NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm3,600,000$2,010,638$0$0$No---------------------------Lien
Seth Jarvis (contrat à 1 volet)Pittsburgh PenguinsRW232002-02-01CANYes174 Lbs5 ft10NoNoProspectNoNo22025-10-07FalseFalsePro & Farm4,680,000$2,613,830$0$0$No4,680,000$--------4,680,000$--------No--------Lien
Tom KuhnhacklPittsburgh PenguinsLW331992-01-21DEUNo196 Lbs6 ft2NoNoFree AgentNoNo12025-10-24FalseFalsePro & Farm850,000$474,734$0$0$No---------------------------
Tomas NosekPittsburgh PenguinsC321992-09-01CZENo205 Lbs6 ft3NoNoFree AgentNoNo22025-11-01FalseFalsePro & Farm700,000$390,957$0$0$No700,000$--------700,000$--------No--------Lien
Vladislav GavrikovPittsburgh PenguinsD291995-11-21RUSNo214 Lbs6 ft3NoNoAssign ManuallyNoNo12025-09-30FalseFalsePro & Farm1,350,000$753,989$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2228.36198 Lbs6 ft11.593,066,169$

Somme salaire 1e année Somme salaire 2e année Somme salaire 3e année Somme salaire 4e année Somme salaire 5e année
67,455,715$23,665,715$11,785,715$0$0$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matt BoldyKasperi KapanenSeth Jarvis31005
2Jack HughesRyan Nugent-HopkinsJordan Kyrou31005
3Tom KuhnhacklJoel Eriksson EkRasmus Asplund31005
4Tomas NosekDominic ToninatoNick Ritchie7023
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Josh MorrisseyBrandon Carlo40023
2Martin FehervaryVladislav Gavrikov34023
3Jonas SiegenthalerCalen Addison26023
4Jonas SiegenthalerCalen Addison0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matt BoldyKasperi KapanenJack Hughes60005
2Nick RitchieJoel Eriksson EkJordan Kyrou40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ryan Nugent-HopkinsJosh Morrissey60014
2Seth JarvisCalen Addison40014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Joel Eriksson EkMatt Boldy60041
2Ryan Nugent-HopkinsNick Ritchie40041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Josh MorrisseyBrandon Carlo60140
2Martin FehervaryVladislav Gavrikov40140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Joel Eriksson Ek60050Josh MorrisseyBrandon Carlo60140
2Ryan Nugent-Hopkins40050Martin FehervaryVladislav Gavrikov40140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Joel Eriksson EkSeth Jarvis60014
2Ryan Nugent-HopkinsMatt Boldy40014
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Josh MorrisseyMartin Fehervary60023
2Calen AddisonBrandon Carlo40023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jack HughesKasperi KapanenJordan KyrouRyan Nugent-HopkinsJosh Morrissey
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matt BoldyRyan Nugent-HopkinsJordan KyrouBrandon CarloJosh Morrissey
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nick Ritchie, Matt Boldy, Jordan KyrouNick Ritchie, Jordan KyrouMatt Boldy
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jonas Siegenthaler, Calen Addison, Vladislav GavrikovMartin FehervaryJonas Siegenthaler, Vladislav Gavrikov
Tirs de pénalité
Jack Hughes, Ryan Nugent-Hopkins, Jordan Kyrou, Matt Boldy, Seth Jarvis
Gardien
#1 : Connor Hellebuyck, #2 : Petr Mrazek
Lignes d’attaque personnalisées en prolongation
Kasperi Kapanen, Jack Hughes, Ryan Nugent-Hopkins, Jordan Kyrou, Joel Eriksson Ek, Matt Boldy, Seth Jarvis, Nick Ritchie, Dominic Toninato, Tom Kuhnhackl
Lignes de défense personnalisées en prolongation
Josh Morrissey, Calen Addison, Brandon Carlo, Martin Fehervary, Vladislav Gavrikov


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
1Boston Bruins22000000844110000004221100000042261.000812200011605223141506518323710220.00%11281.82%038976850.65%38175850.26%25248152.39%412244193317
2Carolina Hurricanes211000006511010000023-11100000042230.5006101600132062132722059203558700.00%10280.00%038976850.65%38175850.26%25248152.39%452639173417
3Chicago Blackhawks1010000013-21010000013-20000000000000.00012300001019658032111020100.00%50100.00%038976850.65%38175850.26%25248152.39%199229188
4Colorado Avalanche11000000422000000000001100000042231.00046100003103391590319182311100.00%4175.00%038976850.65%38175850.26%25248152.39%2213219167
5Columbus Blue Jackets1010000012-1000000000001010000012-100.000123000100381513100317618100.00%30100.00%038976850.65%38175850.26%25248152.39%2417207147
6Detroit Red Wings1010000023-1000000000001010000023-100.0002350001102911108036131819200.00%4250.00%038976850.65%38175850.26%25248152.39%2112228167
7Edmonton Oilers1010000014-31010000014-30000000000000.000123000010197570374815200.00%40100.00%038976850.65%38175850.26%25248152.39%2012238167
8Florida Panthers20200000410-61010000016-51010000034-100.0004711001300672720200671626381100.00%8450.00%238976850.65%38175850.26%25248152.39%432342183419
9Hamilton Mustangs1010000034-1000000000001010000034-100.00035800102036121113033156175120.00%3233.33%038976850.65%38175850.26%25248152.39%2113228157
10Los Angeles Kings11000000615110000006150000000000031.00061016002220357217034923294125.00%4175.00%038976850.65%38175850.26%25248152.39%2213207168
11Montreal Canadiens11000000642000000000001100000064231.00061117001230461110250241045192150.00%5260.00%038976850.65%38175850.26%25248152.39%2314207168
12New Jersey Devils2010100045-11010000024-21000100021120.3334711001111632020212681819416116.67%80100.00%138976850.65%38175850.26%25248152.39%412344173517
13New York Islanders321000001183211000006601100000052360.667111930002270973219460823138697228.57%14192.86%038976850.65%38175850.26%25248152.39%674060265124
14New York Rangers211000003301010000002-21100000031230.50036900120052202390511917359111.11%6266.67%038976850.65%38175850.26%25248152.39%412342183618
15Ottawa Senators21001000853100010005411100000031250.83381220004121502411123622431376116.67%8187.50%038976850.65%38175850.26%25248152.39%432543173317
16Philadelphia Flyers2010100046-2100010003211010000014-320.33347110001216014271726421153810110.00%5180.00%038976850.65%38175850.26%25248152.39%462744183316
17Quebec Nordiques1010000035-21010000035-20000000000000.000358001020371072003379334125.00%20100.00%038976850.65%38175850.26%25248152.39%2414198167
18Seattle Kraken11000000422110000004220000000000031.00047110001302971111024126264125.00%3233.33%038976850.65%38175850.26%25248152.39%2414178189
19St Louis Blues11000000431110000004310000000000031.0004711003100246144030101726200.00%6183.33%138976850.65%38175850.26%25248152.39%2112219178
20Tampa Bay Lightning2010010047-31010000024-21000010023-110.167471100211057221718054191647200.00%8275.00%038976850.65%38175850.26%25248152.39%442641163416
21Toronto Maple Leafs21001000523110000003121000100021150.833591400121156122320159242938900.00%7185.71%138976850.65%38175850.26%25248152.39%412244173417
22Vegas Golden Knights1010000023-1000000000001010000023-100.00024600011031914803288164125.00%4175.00%038976850.65%38175850.26%25248152.39%2012238158
23Winnipeg Jets10001000321000000000001000100032120.6673690011013571585281410253133.33%50100.00%038976850.65%38175850.26%25248152.39%2414198178
Total34131505100979341769020004752-517760310050419500.4909716626300233039510273243523381310363394427241121614.29%1372879.56%538976850.65%38175850.26%25248152.39%747437722300577287
_Since Last GM Reset34131505100979341769020004752-517760310050419500.4909716626300233039510273243523381310363394427241121614.29%1372879.56%538976850.65%38175850.26%25248152.39%747437722300577287
_Vs Conference2491004100696811237020003139-812630210038299360.500691171860017192947352402292588721242318507881112.50%952078.95%438976850.65%38175850.26%25248152.39%526304509212410207
_Vs Division933030002926341102000141225220100015141150.55629497800861232858389107627510113518236513.89%30776.67%138976850.65%38175850.26%25248152.39%2011181937715075

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3450L2971662631027103633944272400
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
34131551009793
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
176920004752
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
177631005041
Derniers 10 matchs
WLOTWOTL SOWSOL
540100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1121614.29%1372879.56%5
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
324352338132330395
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
38976850.65%38175850.26%25248152.39%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
747437722300577287


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
13Pittsburgh Penguins6Montreal Canadiens4WSommaire du match
317Pittsburgh Penguins3Hamilton Mustangs4LSommaire du match
531Pittsburgh Penguins1Philadelphia Flyers4LSommaire du match
745Ottawa Senators4Pittsburgh Penguins5WXSommaire du match
963Tampa Bay Lightning4Pittsburgh Penguins2LSommaire du match
1171Pittsburgh Penguins2Toronto Maple Leafs1WXSommaire du match
1387Quebec Nordiques5Pittsburgh Penguins3LSommaire du match
15103Chicago Blackhawks3Pittsburgh Penguins1LSommaire du match
17114St Louis Blues3Pittsburgh Penguins4WSommaire du match
19128Pittsburgh Penguins3Winnipeg Jets2WXSommaire du match
23147Pittsburgh Penguins4Boston Bruins2WSommaire du match
26160Pittsburgh Penguins3Florida Panthers4LSommaire du match
29174Carolina Hurricanes3Pittsburgh Penguins2LSommaire du match
32190New York Islanders3Pittsburgh Penguins5WSommaire du match
36208New York Rangers2Pittsburgh Penguins0LSommaire du match
39222Pittsburgh Penguins2New Jersey Devils1WXSommaire du match
42236New Jersey Devils4Pittsburgh Penguins2LSommaire du match
45247Pittsburgh Penguins3New York Rangers1WSommaire du match
48261Pittsburgh Penguins5New York Islanders2WSommaire du match
50272Pittsburgh Penguins4Carolina Hurricanes2WSommaire du match
53286Florida Panthers6Pittsburgh Penguins1LSommaire du match
56302Boston Bruins2Pittsburgh Penguins4WSommaire du match
60320Pittsburgh Penguins1Columbus Blue Jackets2LSommaire du match
62331Los Angeles Kings1Pittsburgh Penguins6WSommaire du match
64344Seattle Kraken2Pittsburgh Penguins4WSommaire du match
66362Pittsburgh Penguins2Vegas Golden Knights3LSommaire du match
68367Toronto Maple Leafs1Pittsburgh Penguins3WSommaire du match
70387Pittsburgh Penguins2Tampa Bay Lightning3LXSommaire du match
72402Pittsburgh Penguins3Ottawa Senators1WSommaire du match
73409Philadelphia Flyers2Pittsburgh Penguins3WXSommaire du match
77433Edmonton Oilers4Pittsburgh Penguins1LSommaire du match
79447Pittsburgh Penguins4Colorado Avalanche2WSommaire du match
81461Pittsburgh Penguins2Detroit Red Wings3LSommaire du match
83468New York Islanders3Pittsburgh Penguins1LSommaire du match
85479New York Rangers-Pittsburgh Penguins-
88495Pittsburgh Penguins-New Jersey Devils-
92517Pittsburgh Penguins-Anaheim Mighty Ducks-
93524Anaheim Mighty Ducks-Pittsburgh Penguins-
95538California Golden Seals-Pittsburgh Penguins-
98559Pittsburgh Penguins-California Golden Seals-
100573Pittsburgh Penguins-San Jose Sharks-
102587Vancouver Canucks-Pittsburgh Penguins-
105601Hamilton Mustangs-Pittsburgh Penguins-
108616Montreal Canadiens-Pittsburgh Penguins-
111630Pittsburgh Penguins-Quebec Nordiques-
113639Pittsburgh Penguins-Boston Bruins-
116653Pittsburgh Penguins-Florida Panthers-
120672Carolina Hurricanes-Pittsburgh Penguins-
122679Pittsburgh Penguins-Seattle Kraken-
123691Pittsburgh Penguins-Los Angeles Kings-
125707Columbus Blue Jackets-Pittsburgh Penguins-
127721Winnipeg Jets-Pittsburgh Penguins-
130739Pittsburgh Penguins-St Louis Blues-
132751Pittsburgh Penguins-Chicago Blackhawks-
134757Toronto Maple Leafs-Pittsburgh Penguins-
136777Tampa Bay Lightning-Pittsburgh Penguins-
138787Ottawa Senators-Pittsburgh Penguins-
140801Pittsburgh Penguins-Philadelphia Flyers-
144821Vegas Golden Knights-Pittsburgh Penguins-
146832Pittsburgh Penguins-Edmonton Oilers-
149848Colorado Avalanche-Pittsburgh Penguins-
151859Detroit Red Wings-Pittsburgh Penguins-
154881San Jose Sharks-Pittsburgh Penguins-
156895Pittsburgh Penguins-Vancouver Canucks-
159909Pittsburgh Penguins-New York Islanders-
161921Pittsburgh Penguins-New York Rangers-
163937New Jersey Devils-Pittsburgh Penguins-
165951Pittsburgh Penguins-Carolina Hurricanes-
167965Florida Panthers-Pittsburgh Penguins-
169980Boston Bruins-Pittsburgh Penguins-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
172988Pittsburgh Penguins-Toronto Maple Leafs-
1741006Pittsburgh Penguins-Tampa Bay Lightning-
1761021Pittsburgh Penguins-Ottawa Senators-
1781032Philadelphia Flyers-Pittsburgh Penguins-
1801039Hamilton Mustangs-Pittsburgh Penguins-
1811053Pittsburgh Penguins-Hamilton Mustangs-
1831067Pittsburgh Penguins-Montreal Canadiens-
1841081Montreal Canadiens-Pittsburgh Penguins-
1861095Quebec Nordiques-Pittsburgh Penguins-
1871116Pittsburgh Penguins-Quebec Nordiques-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité59404860198039601260
Prix des billets92513023186
Assistance80,52365,34328,83053,07917,041
Attendance PCT79.74%79.09%85.65%78.85%79.56%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
23 14401 - 80.01% 1,044,442$17,755,506$18000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineursValeur du plafond salarial spécial
29,892,167$ 68,605,715$ 0$ 0$ 0$
Plafond salarial par jourPlafond salarial à ce jourTaxe de luxe totaleJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 29,892,167$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
24,022,155$ 105 364,924$ 38,317,020$

Total de l’équipe estimé
Dépenses de la saison estimées Compte bancaire actuel Compte bancaire projeté
39,410,910$ 127,916,041$ 113,882,718$



Charte de profondeur

Ailier gaucheCentreAilier droit
Jake GuentzelAGE:30PO:55OV:81
Jack HughesAGE:24PO:40OV:81
Matt BoldyAGE:24PO:55OV:79
Bobby Brink (R)AGE:23PO:55OV:72
Tom KuhnhacklAGE:33PO:55OV:69
Axel Jonsson-FjallbyAGE:27PO:55OV:68
Dominik SimonAGE:30PO:55OV:68
Oskar SundqvistAGE:31PO:55OV:66
Jack StudnickaAGE:26PO:55OV:64
Kasperi KapanenAGE:28PO:55OV:80
Ryan Nugent-HopkinsAGE:32PO:55OV:77
Joel Eriksson EkAGE:28PO:55OV:76
Marco Rossi (R)AGE:23PO:55OV:74
Ridly Greig (R)AGE:22PO:55OV:74
Dominic ToninatoAGE:31PO:55OV:68
Jiri Kulich (R)AGE:21PO:55OV:68
Greg McKeggAGE:33PO:55OV:66
Dennis RasmussenAGE:34PO:55OV:65
Tomas NosekAGE:32PO:55OV:65
Jordan KyrouAGE:27PO:55OV:80
Seth Jarvis (R)AGE:23PO:55OV:78
Kirill Marchenko (R)AGE:24PO:55OV:76
Matt Coronato (R)AGE:22PO:55OV:72
Nick RitchieAGE:29PO:55OV:72
Rasmus AsplundAGE:27PO:55OV:70
Martin FrkAGE:31PO:55OV:65
Trey Fix-WolanskyAGE:26PO:55OV:65
Kyle CriscuoloAGE:33PO:55OV:64

Défense #1Défense #2Gardien
Josh MorrisseyAGE:30PO:55OV:82
Brandon CarloAGE:28PO:55OV:80
Martin FehervaryAGE:25PO:55OV:80
Calen AddisonAGE:25PO:55OV:76
Vladislav GavrikovAGE:29PO:55OV:75
Jonas SiegenthalerAGE:28PO:55OV:74
Joe MorrowAGE:32PO:55OV:73
Juuso ValimakiAGE:26PO:55OV:72
Kris LetangAGE:38PO:55OV:72
Nick DeSimoneAGE:30PO:55OV:70
NICLAS ALMARIAGE:27PO:52OV:70
Paul LaDueAGE:32PO:55OV:67
Juuso RiikolaAGE:31PO:55OV:66
EETU PELTOLAAGE:25PO:52OV:66
Jack RathboneAGE:26PO:55OV:65
Ethan ProwAGE:32PO:55OV:64
Ashton SautnerAGE:31PO:75OV:63
Connor HellebuyckAGE:32PO:55OV:81
Petr MrazekAGE:33PO:55OV:80
Reto BerraAGE:38PO:55OV:76
STEFANOS LEKKASAGE:29PO:52OV:72
TIM JUELAGE:30PO:52OV:72

Espoirs

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
EspoirNom de l’équipeAnnée de repêchageChoix totalInformationDate de la Dernière TransactionLien
0x LTCsPittsburgh Penguins000Lien
1 000 000 NSHL25 Waiver BucksPittsburgh Penguins00
1x NSHL26 ODW ClaimPittsburgh Penguins000Lien
1x RFA TagPittsburgh Penguins000Lien
20x TC PTSPittsburgh Penguins000Lien
Aaron HuglenPittsburgh Penguins191250Lien
Adam JiricekPittsburgh Penguins24230Lien
Adam SykoraPittsburgh Penguins22530Lien
Akil ThomasPittsburgh Penguins18460Lien
Aleksandr KisakovPittsburgh Penguins21690Lien
Aleksi HeimosalmiPittsburgh Penguins21600Lien
Alexander NikishinPittsburgh Penguins22260Lien
Andrew StrathmannPittsburgh Penguins231520Lien
Anton JohanssonPittsburgh Penguins251920Lien
Beau AkeyPittsburgh Penguins23960Lien
Ben DanfordPittsburgh Penguins24630Lien
Brandon SvobodaPittsburgh Penguins231690Lien
Daemon HuntPittsburgh Penguins21630Lien
Daniil ProkhorovPittsburgh Penguins25490Lien
David EdstromPittsburgh Penguins23460Lien
Dmitry OvchinnikovPittsburgh Penguins201030Lien
Donovan SebrangoPittsburgh Penguins221600Lien
Elmer SoderblomPittsburgh Penguins211130Lien
Eriks MateikoPittsburgh Penguins241070Lien
Ethan GauthierPittsburgh Penguins23470Lien
Etienne MorinPittsburgh Penguins23670Lien
Filip LindbergPittsburgh Penguins211150Lien
Grigori DenisenkoPittsburgh Penguins18290Lien
Helge GransPittsburgh Penguins20360Lien
Hendrix LapierrePittsburgh Penguins20240Lien
Ilya FedotovPittsburgh Penguins211160Lien
Isak RosenPittsburgh Penguins21180Lien
Jack Hughes DOB 2003Pittsburgh Penguins22510Lien
Jayden PerronPittsburgh Penguins23720Lien
Jordan GustafsonPittsburgh Penguins221350Lien
Jordy BellerivePittsburgh Penguins18510Lien
Julius MiettinenPittsburgh Penguins24490Lien
Julius SumpfPittsburgh Penguins251350Lien
Juraj PekarcikPittsburgh Penguins231200Lien
Justin KipkiePittsburgh Penguins251640Lien
Kirill KirsanovPittsburgh Penguins22480Lien
Ludwig PerssonPittsburgh Penguins221370Lien
Martin ChromiakPittsburgh Penguins20880Lien
Matej BlumelPittsburgh Penguins221520Lien
Matyas SapovalivPittsburgh Penguins22890Lien
Max PlantePittsburgh Penguins24870Lien
Miroslav HolinkaPittsburgh Penguins25780Lien
Oliver MoorePittsburgh Penguins23160Lien
Peyton KettlesPittsburgh Penguins25570Lien
Philippe DesrosiersPittsburgh Penguins13870Lien
Prokhor PoltapovPittsburgh Penguins21500Lien
Radim MrtkaPittsburgh Penguins25250Lien
Raphael LavoiePittsburgh Penguins19230Lien
Ryan ChesleyPittsburgh Penguins22410Lien
Ryan GreenePittsburgh Penguins221120Lien
Sam O'ReillyPittsburgh Penguins24380Lien
Sampo RantaPittsburgh Penguins181050Lien
Samuel PoulinPittsburgh Penguins19340Lien
Yegor BorikovPittsburgh Penguins251060Lien
Yevgeni VolokhinPittsburgh Penguins241110Lien
Zach NehringPittsburgh Penguins231620Lien
Zion NybeckPittsburgh Penguins20770Lien

Choix au repêchage

Année R1R2R3R4R5R6R7
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Choix au repêchage conditionnel




La base de données des nouvelles du STHS n'a pas été trouvée ou corrompu. Veuillez en créer une de la section Gestion des nouvelles de la ligue du site web en étant connecté comme commissaire.




Pittsburgh Penguins Historique de transactions

[2026-03-19 3:54:30 PM] TRADE : From Toronto Maple Leafs to Pittsburgh Penguins : TIM JUEL (72).
[2026-03-19 3:54:30 PM] TRADE : From Pittsburgh Penguins to Toronto Maple Leafs : $25,000 (Money).
[2026-02-07 3:08:51 PM] New Record for Team's Most Hits (33) in 1 Game for Pittsburgh Penguins!
[2026-02-05 1:28:01 PM] New Record for Team's Most Shots Blocked (19) in 1 Game for Pittsburgh Penguins!
[2026-02-05 1:28:01 PM] New Record for Team's Most Shots Blocked (19) in 1 Game for Pittsburgh Penguins!
[2026-02-03 3:12:01 PM] New Record for Team's Most Hits (25) in 1 Game for Pittsburgh Penguins!



Oskar Sundqvist est dehors pour 6 jours à cause de Right Eye Injury.



Pittsburgh Penguins 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

Pittsburgh Penguins 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

Pittsburgh Penguins 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

Pittsburgh Penguins 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

Pittsburgh Penguins 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