Penguins

GP: 64 | W: 35 | L: 27 | OTL: 2 | P: 72
GF: 344 | GA: 326 | PP%: 45.58% | PK%: 57.60%
DG: Jeremy Lyrette | Morale : 56 | Moyenne d'Équipe : 67
Prochain matchs #773 vs Thunderbird
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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 SP
1Josh LeivoX100.005640837178764465716762626452516163690
2Melker KarlssonX100.006842797665828971975459706960553661680
3Anthony BeauvillierXXX100.006841827964779070715668647155538066670
4Matthew PecaX100.005542767758689075876064676051514769670
5Jacob de la RoseX100.008142787181767064685156766754547774660
6Jesse PuljujarviX100.006841827783819077505064597153529176660
7Jimmy HayesX100.007140837186786474635457626563575574660
8Zach Aston-ReeseXXX100.006144707672668076654866656350504374650
9Kailer YamamotoX100.006040898449833880505750596050508474630
10Jeremy Bracco (R)X100.004841776039587960506455605550504474600
11Jake DotchinX100.007943807481797676305355726853544856700
12Mike ReillyX100.006442797274747477306053706654526064680
13Roland McKeownX100.006043717472539757305750605650507274620
Rayé
MOYENNE D'ÉQUIPE100.00654279746973757159565865645352616966
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 SP
1Casey DeSmith100.00777878738483828484767451643724750
2Alex Nedeljkovic (R)100.00727474797267757373716950617679690
Rayé
MOYENNE D'ÉQUIPE100.0075767676787579797974725163575272
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Benoit Groulx61968380735870CAN504300,000$


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'ÉquipePOS GP 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
1Jimmy HayesPenguins (Pit)RW55636112410175684638912725116.20%37122022.20353166771880002189463.04%469543082.03000011674
2Jesse PuljujarviPenguins (Pit)RW5640529224221041312708314614.81%2779714.231213252477000003359.38%648125012.31000024127
3Matthew PecaPenguins (Pit)C574151922526032572286813317.98%3180814.1810162626720001235270.68%13543726002.2800000777
4Jacob de la RosePenguins (Pit)LW5615365126360603782214618.29%3982014.65471113742026232167.71%962024001.2400000128
5Melker KarlssonPenguins (Pit)C1423163910195214198336123.47%936826.34991814341017414074.27%3772212032.1100001601
6Zach Aston-ReesePenguins (Pit)C/LW/RW56221638-143403648144428415.28%2262111.1062810250000141069.49%4953518001.2200000112
7Roland McKeownPenguins (Pit)D56132331654030218335311.20%4991816.4006632701133600100.00%1735000.7200000023
8Jeremy BraccoPenguins (Pit)RW5681422-18140283111454857.02%2176513.6711223000000156.67%301724000.5701000013
9Kailer YamamotoPenguins (Pit)RW5641721-134020237023475.71%165079.06224311000031057.14%213512000.8300000000
10Mike ReillyPenguins (Pit)D1541418421510154815178.33%2141927.9548129450228461050.00%21228000.8600001010
11Josh LeivoPenguins (Pit)LW119514000181235131925.71%520118.353254301011210064.29%1477001.3900000102
12Anthony BeauvillierPenguins (Pit)C/LW/RW656114207937111913.51%216126.873365130001211056.52%23114001.3600000020
13Jake DotchinPenguins (Pit)D6347420117122725.00%1416627.78325314000024000.00%0312000.8400000001
Stats d'équipe Total ou en Moyenne5002383245627825125382378161052794614.78%293777615.559210219419361843729274271170.00%25233822700121.4501005363538
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
1Alex NedeljkovicPenguins (Pit)2923500.9093.1517172090990529710.0000290112
Stats d'équipe Total ou en Moyenne2923500.9093.1517172090990529710.0000290112


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Alex NedeljkovicPenguins (Pit)G211996-01-07Yes198 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Anthony BeauvillierPenguins (Pit)C/LW/RW201997-06-08No182 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm894,166$0$0$NoLien
Casey DeSmithPenguins (Pit)G261991-08-13No181 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jacob de la RosePenguins (Pit)LW221995-05-20No210 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm900,000$0$0$NoLien
Jake DotchinPenguins (Pit)D231994-03-24No210 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm812,500$0$0$NoLien
Jeremy BraccoPenguins (Pit)RW201997-03-17Yes171 Lbs5 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jesse PuljujarviPenguins (Pit)RW191998-05-07No211 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm925,000$0$0$NoLien
Jimmy HayesPenguins (Pit)RW271989-11-21No215 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Josh LeivoPenguins (Pit)LW241993-05-26No210 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Kailer YamamotoPenguins (Pit)RW191998-09-29No154 Lbs5 ft8NoNoNo2Contrat d'EntréePro & Farm925,000$0$0$NoLien
Matthew PecaPenguins (Pit)C241993-04-27No178 Lbs5 ft8NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Melker KarlssonPenguins (Pit)C271990-07-18No180 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm2,000,000$0$0$NoLien
Mike ReillyPenguins (Pit)D241993-07-13No195 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Roland McKeownPenguins (Pit)D211996-01-20No195 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Zach Aston-ReesePenguins (Pit)C/LW/RW231994-08-10No204 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm925,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1522.67193 Lbs6 ft01.20892,111$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jimmy Hayes40122
2Jacob de la RoseMatthew PecaJesse Puljujarvi30122
3Jeremy BraccoZach Aston-ReeseKailer Yamamoto20122
4Jeremy Bracco10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
2Roland McKeown30122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jimmy Hayes60122
2Jacob de la RoseMatthew PecaJesse Puljujarvi40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Roland McKeown40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Matthew PecaJimmy Hayes40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Roland McKeown40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
240122Roland McKeown40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Matthew PecaJimmy Hayes40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Roland McKeown40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jimmy Hayes
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jimmy Hayes
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Zach Aston-Reese, Kailer Yamamoto, Jacob de la RoseZach Aston-Reese, Kailer YamamotoJacob de la Rose
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Roland McKeown, , Roland McKeown,
Tirs de Pénalité
, , Matthew Peca, Jimmy Hayes, Jacob de la Rose
Gardien
#1 : , #2 :


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
LigueDomicileVisiteur
# 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
1Admirals211000001417-311000000107310100000410-620.500142438005014814516761779477038923282713323.08%14750.00%1769122462.83%711127255.90%834138060.43%142187013935321030524
2Barracuda11000000651000000000001100000065121.00061016005014814514361779477031488134125.00%4325.00%0769122462.83%711127255.90%834138060.43%142187013935321030524
3Bears3300000017710110000008352200000094561.000172946005014814519561779477037328304815533.33%10370.00%0769122462.83%711127255.90%834138060.43%142187013935321030524
4Blacknight3210000017981100000073421100000106440.6671729460050148145193617794770360202843171058.82%14378.57%0769122462.83%711127255.90%834138060.43%142187013935321030524
5Bruins44000000339242200000018513220000001541181.000335285005014814511486177947703113294158241562.50%18383.33%2769122462.83%711127255.90%834138060.43%142187013935321030524
6Condors20101000716-91000100043110100000313-1020.50071320005014814517861779477039226203010330.00%10640.00%0769122462.83%711127255.90%834138060.43%142187013935321030524
7Crunch321000001713411000000615211000001112-140.66717284500501481451104617794770310342274111327.27%11372.73%2769122462.83%711127255.90%834138060.43%142187013935321030524
8Devils633000002631-5312000001014-4321000001617-160.50026467210501481451180617794770325388726820840.00%311648.39%0769122462.83%711127255.90%834138060.43%142187013935321030524
9Gulls1010000056-1000000000001010000056-100.000581300501481451346177947703187415100.00%2150.00%2769122462.83%711127255.90%834138060.43%142187013935321030524
10Heat2200000015781100000051411000000106441.00015254000501481451886177947703441120159555.56%10370.00%0769122462.83%711127255.90%834138060.43%142187013935321030524
11Icedogs211000001113-2110000006511010000058-320.50011172800501481451516177947703532416216350.00%8362.50%0769122462.83%711127255.90%834138060.43%142187013935321030524
12Monsters522001002424021100000880311001001616050.500244367005014814511546177947703122353468231356.52%17758.82%0769122462.83%711127255.90%834138060.43%142187013935321030524
13Moose2110000012751010000036-31100000091820.500122032005014814519561779477036030202710660.00%10460.00%2769122462.83%711127255.90%834138060.43%142187013935321030524
14Phantoms65100000403373300000023158321000001718-1100.83340701100050148145120461779477032351205477291758.62%281739.29%0769122462.83%711127255.90%834138060.43%142187013935321030524
15Rampages20200000716-91010000049-51010000037-400.0007132000501481451716177947703823118258112.50%9366.67%0769122462.83%711127255.90%834138060.43%142187013935321030524
16Reigh220000001468110000007341100000073441.000142034005014814517661779477036515161611654.55%80100.00%0769122462.83%711127255.90%834138060.43%142187013935321030524
17Rocket20200000712-520200000712-50000000000000.0007111800501481451766177947703692714228225.00%7271.43%0769122462.83%711127255.90%834138060.43%142187013935321030524
18Senateurs413000001520-520200000611-52110000099020.25015264100501481451130617794770319658384015746.67%20955.00%0769122462.83%711127255.90%834138060.43%142187013935321030524
19Sound Tigers413000001825-7312000001414010100000411-720.25018304800501481451126617794770316448344316637.50%171229.41%0769122462.83%711127255.90%834138060.43%142187013935321030524
20Stars20200000517-121010000039-61010000028-600.00051015005014814516761779477031063222248337.50%11736.36%0769122462.83%711127255.90%834138060.43%142187013935321030524
21Thunderbird53100100322483210000016133210001001611570.700325486005014814511726177947703158613663221150.00%18666.67%0769122462.83%711127255.90%834138060.43%142187013935321030524
Total64342701200344326183217140100016715116321713002001771752720.5633445829261050148145121846177947703220678159279628312945.58%28312057.60%9769122462.83%711127255.90%834138060.43%142187013935321030524
23Wolves1010000029-71010000029-70000000000000.00024600501481451326177947703371812123133.33%6266.67%0769122462.83%711127255.90%834138060.43%142187013935321030524
_Since Last GM Reset64342701200344326183217140100016715116321713002001771752720.5633445829261050148145121846177947703220678159279628312945.58%28312057.60%9769122462.83%711127255.90%834138060.43%142187013935321030524
_Vs Conference4224160020022919831221210000001169620201260020011310211500.595229389618105014814511389617794770314865363805281838747.54%1777855.93%4769122462.83%711127255.90%834138060.43%142187013935321030524
_Vs Division24149001001251205127500000635491274001006266-4290.6041252183431050148145175961779477038473192243041034947.57%1035546.60%0769122462.83%711127255.90%834138060.43%142187013935321030524

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
6472L13445829262184220678159279610
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6434271200344326
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3217141000167151
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3217130200177175
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
28312945.58%28312057.60%9
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
6177947703501481451
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
769122462.83%711127255.90%834138060.43%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
142187013935321030524


Derniers Match 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
3 - 2018-10-1111Phantoms3Penguins7WSommaire du Match
5 - 2018-10-1320Penguins4Phantoms1WSommaire du Match
8 - 2018-10-1630Penguins1Devils8LSommaire du Match
12 - 2018-10-2040Devils6Penguins3LSommaire du Match
18 - 2018-10-2660Monsters4Penguins2LSommaire du Match
21 - 2018-10-2976Thunderbird9Penguins6LSommaire du Match
24 - 2018-11-0187Penguins4Bears2WSommaire du Match
26 - 2018-11-0398Penguins4Sound Tigers11LSommaire du Match
27 - 2018-11-04103Penguins4Monsters6LSommaire du Match
29 - 2018-11-06114Sound Tigers4Penguins3LSommaire du Match
32 - 2018-11-09131Penguins9Thunderbird3WSommaire du Match
33 - 2018-11-10137Bears3Penguins8WSommaire du Match
37 - 2018-11-14157Phantoms6Penguins8WSommaire du Match
39 - 2018-11-16167Penguins7Blacknight2WSommaire du Match
41 - 2018-11-18176Devils4Penguins2LSommaire du Match
47 - 2018-11-24197Penguins2Stars8LSommaire du Match
49 - 2018-11-26205Reigh3Penguins7WSommaire du Match
51 - 2018-11-28212Penguins9Moose1WSommaire du Match
54 - 2018-12-01226Bruins2Penguins9WSommaire du Match
56 - 2018-12-03231Penguins8Bruins2WSommaire du Match
60 - 2018-12-07243Penguins5Crunch2WSommaire du Match
62 - 2018-12-09252Sound Tigers3Penguins5WSommaire du Match
64 - 2018-12-11257Penguins8Monsters5WSommaire du Match
67 - 2018-12-14269Penguins5Icedogs8LSommaire du Match
69 - 2018-12-16280Penguins7Bruins2WSommaire du Match
70 - 2018-12-17287Thunderbird1Penguins6WSommaire du Match
74 - 2018-12-21305Condors3Penguins4WXSommaire du Match
76 - 2018-12-23312Penguins8Devils3WSommaire du Match
80 - 2018-12-27330Crunch1Penguins6WSommaire du Match
82 - 2018-12-29340Penguins7Reigh3WSommaire du Match
84 - 2018-12-31350Penguins5Bears2WSommaire du Match
86 - 2019-01-02356Devils4Penguins5WSommaire du Match
89 - 2019-01-05373Penguins2Senateurs3LSommaire du Match
90 - 2019-01-06380Heat1Penguins5WSommaire du Match
94 - 2019-01-10395Penguins7Senateurs6WSommaire du Match
96 - 2019-01-12401Penguins3Blacknight4LSommaire du Match
97 - 2019-01-13407Bruins3Penguins9WSommaire du Match
102 - 2019-01-18427Senateurs6Penguins4LSommaire du Match
104 - 2019-01-20436Penguins4Admirals10LSommaire du Match
107 - 2019-01-23451Rocket3Penguins2LSommaire du Match
109 - 2019-01-25458Penguins10Heat6WSommaire du Match
112 - 2019-01-28473Penguins6Barracuda5WSommaire du Match
114 - 2019-01-30479Admirals7Penguins10WSommaire du Match
116 - 2019-02-01485Penguins4Monsters5LXSommaire du Match
118 - 2019-02-03495Penguins3Condors13LSommaire du Match
120 - 2019-02-05503Monsters4Penguins6WSommaire du Match
127 - 2019-02-12527Blacknight3Penguins7WSommaire du Match
131 - 2019-02-16546Penguins3Phantoms10LSommaire du Match
132 - 2019-02-17552Rocket9Penguins5LSommaire du Match
136 - 2019-02-21572Thunderbird3Penguins4WSommaire du Match
138 - 2019-02-23582Penguins7Thunderbird8LXSommaire du Match
141 - 2019-02-26596Sound Tigers7Penguins6LSommaire du Match
146 - 2019-03-03614Penguins5Gulls6LSommaire du Match
147 - 2019-03-04621Stars9Penguins3LSommaire du Match
150 - 2019-03-07637Penguins10Phantoms7WSommaire du Match
152 - 2019-03-09646Phantoms6Penguins8WSommaire du Match
155 - 2019-03-12665Icedogs5Penguins6WSommaire du Match
157 - 2019-03-14673Penguins6Crunch10LSommaire du Match
162 - 2019-03-19692Wolves9Penguins2LSommaire du Match
166 - 2019-03-23710Senateurs5Penguins2LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
168 - 2019-03-25718Penguins3Rampages7LSommaire du Match
172 - 2019-03-29735Moose6Penguins3LSommaire du Match
175 - 2019-04-01744Penguins7Devils6WSommaire du Match
179 - 2019-04-05757Rampages9Penguins4LSommaire du Match
183 - 2019-04-09773Penguins-Thunderbird-
185 - 2019-04-11781Barracuda-Penguins-
187 - 2019-04-13792Penguins-Wolves-
191 - 2019-04-17807Marlies-Penguins-
195 - 2019-04-21822Penguins-Bears-
197 - 2019-04-23831Monsters-Penguins-
201 - 2019-04-27845Penguins-Marlies-
202 - 2019-04-28854Penguins-Rocket-
204 - 2019-04-30859Crunch-Penguins-
207 - 2019-05-03871Penguins-Rocket-
209 - 2019-05-05881Bears-Penguins-
214 - 2019-05-10900Bears-Penguins-
218 - 2019-05-14918Marlies-Penguins-
220 - 2019-05-16927Penguins-Marlies-
221 - 2019-05-17931Penguins-Sound Tigers-
227 - 2019-05-23952Gulls-Penguins-
233 - 2019-05-29970Gulls-Penguins-
235 - 2019-05-31983Penguins-Sound Tigers-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,157,995$ 1,338,167$ 1,323,167$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 930,135$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 57 6,912$ 393,984$




LigueDomicileVisiteur
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
264342701200344326183217140100016715116321713002001771752723445829261050148145121846177947703220678159279628312945.58%28312057.60%9769122462.83%711127255.90%834138060.43%142187013935321030524
Total Saison Régulière64342701200344326183217140100016715116321713002001771752723445829261050148145121846177947703220678159279628312945.58%28312057.60%9769122462.83%711127255.90%834138060.43%142187013935321030524