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Capitals
GP: 82 | W: 43 | L: 33 | OTL: 6 | P: 92
GF: 259 | GA: 263 | PP%: 18.85% | PK%: 84.30%
DG: Pierre-Marc Brochu | Morale : 66 | Moyenne d’équipe : 68
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Centre de jeu
Flyers
38-36-8, 84pts
3
FINAL
1 Capitals
43-33-6, 92pts
Team Stats
L1SéquenceW1
19-20-2Fiche domicile23-16-2
19-16-6Fiche domicile20-17-4
5-4-1Derniers 10 matchs7-2-1
2.93Buts par match 3.16
3.16Buts contre par match 3.21
15.00%Pourcentage en avantage numérique18.85%
81.25%Pourcentage en désavantage numérique84.30%
Blues
44-30-8, 96pts
2
FINAL
5 Capitals
43-33-6, 92pts
Team Stats
L1SéquenceW1
25-12-4Fiche domicile23-16-2
19-18-4Fiche domicile20-17-4
5-4-1Derniers 10 matchs7-2-1
3.28Buts par match 3.16
3.28Buts contre par match 3.21
16.81%Pourcentage en avantage numérique18.85%
77.66%Pourcentage en désavantage numérique84.30%
Meneurs d'équipe
Buts
Dominik Simon
36
Passes
Brendan Leipsic
52
Points
Dominik Simon
77
Plus/Moins
Ross Colton
14
Victoires
Joni Ortio
30
Pourcentage d’arrêts
Joni Ortio
0.908

Statistiques d’équipe
Buts pour
259
3.16 GFG
Tirs pour
2660
32.44 Avg
Pourcentage en avantage numérique
18.9%
46 GF
Début de zone offensive
38.7%
Buts contre
263
3.21 GAA
Tirs contre
2606
31.78 Avg
Pourcentage en désavantage numérique
84.3%%
38 GA
Début de la zone défensive
38.1%
Informations de l'équipe

Directeur généralPierre-Marc Brochu
EntraîneurSpencer Carbery
DivisionMétropolitaine
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,407
Billets de saison1,800


Informations de la formation

Équipe Pro35
Équipe Mineure18
Limite contact 53 / 60
Espoirs32


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
1Filip Chytil (R)X100.007250768487848686647979722584766481750241900,000$
2Dominik Simon (R)X100.0062269967727284856586807369827743807302912,000,000$
3Ross Colton (R)X100.008561698179838083867576722581615282730271850,000$
4Brendan Leipsic (R)X100.0062309069707079837189787566706649777202912,000,000$
5Warren Foegele (R)X100.007950757580838481557573762577766481720281900,000$
6Oliver Wahlstrom (R)X100.007260627687837374507476662573665476690233900,000$
7Rafael Harvey-Pinard (R)X100.006740808574876875406674712578585045682253825,000$
8Rudolfs Balcers (R)X100.007944887275687171227470672578766678670272800,000$
9Zack MacEwen (R)X100.008379647385828371556564672571715980670273700,000$
10Alexei Protas (R)X100.007245897294827673497064662571594963670232789,167$
11Michael Sgarbossa (R)X100.008368806976576963817265646287835874660312700,000$
12Axel Jonsson Fjällby (R)X100.007140877579817371406766692572594977660262750,000$
13Ilya Lyubushkin (R)X100.007650707681848374407264872572715977740301900,000$
14Tomas Kundratek (R)X100.0047339962766378985289904672999922707003431,000,000$
15Maxime Lajoie (R)X100.008382637172757961306967735277754883690262700,000$
16Philip Broberg (R)X100.006640887686827370406762732570594979692223863,333$
17Andreas Borgman (R)X100.006238886177807861306259815378734349670281600,000$
18Kyle Capobianco (R)X100.006140757283827167406063642567756524650261575,000$
Rayé
1Colin Blackwell (R)X100.007947856576747863457167715986676340660313700,000$
2Martin Kaut (R)X100.006540827582817370406464652570655519650243575,000$
3Jonah Gadjovich (R)X100.008181567285777069406463652568605319640251783,333$
4Andrew DesjardinsX100.00453199667456776383494884689999119630373575,000$
5Anton Blidh (R)X100.006738916576626862607369642560606220630291575,000$
6Alexander Holtz (R)X100.005640747382806367406163602568585019620222894,167$
7Joe Snively (R)X100.005540727056646360426154612561555019570282800,000$
8Beck Malenstyn (R)X100.006245706166616159405153565825535019542263762,500$
9Logan Stanley (R)X100.006555656796836567406262692566615226660251900,000$
10Cale Fleury (R)X100.006740757283836866406160662566655519650253600,000$
11Tyler Tucker (R)X100.006765627485836569406362672568525019652243808,333$
12Tyler Lewington (R)X100.007869996675696862305550684978722920640291750,000$
13Igor Ozhiganov (R)X100.005825856378636655305451696067662419610312575,000$
14Jordan Spence (R)X100.005340687255626267406654662564505020602233820,000$
MOYENNE D’ÉQUIPE100.00684879717875737048686569377368504966
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
1Niklas Svedberg (R)100.008070707374999999997779999556838403432,000,000$
2Joni Ortio (R)100.007877717575999999997776979347838403311,250,000$
Rayé
1Michael Dipietro (R)100.00796866777479818079797566706320740242575,000$
MOYENNE D’ÉQUIPE100.0079726975749293939278778786556281
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Spencer Carbery6060606055551CAN413750,000$


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
1Dominik SimonCapitals (WAS)LW823641779001111322729314913.24%60172421.041012224121321372034243.20%1694625000.8929000493
2Filip ChytilCapitals (WAS)C70334275489451441962667916312.41%54146820.98716232617912331903348.30%19425535201.02164233106
3Ross ColtonCapitals (WAS)C82363773141629017520729210917112.33%40154518.8577143417500031155456.51%16355718000.9427756815
4Brendan LeipsicCapitals (WAS)LW771952718281093106249671447.63%31143718.67210122215800061032440.91%883533000.9914110632
5Warren FoegeleCapitals (WAS)RW75193049-368301731191716011411.11%35142819.059514371950002515250.57%873533100.6904420303
6Oliver WahlstromCapitals (WAS)RW82153348111174520311016641979.04%34143417.502101216175000001043.21%813820000.6701243213
7Tomas KundratekCapitals (WAS)D7843943-2555213516453712.44%81187724.0711415242250003235000%04643100.4602100023
8Alexei ProtasCapitals (WAS)C82181230-3011586109164387710.98%39109913.410001310000111139.15%8433011000.5500010110
9Rudolfs BalcersCapitals (WAS)RW82111829-131610928012035679.17%1985810.48000015000062215.38%523014000.6801011133
10Maxime LajoieCapitals (WAS)D827222922441201471238624358.14%108167520.4311251380000133100%01454000.350110410101
11Ilya LyubushkinCapitals (WAS)D7462329-592201641578132277.41%122173523.46448152090000179200%01355000.3302013121
12Axel Jonsson FjällbyCapitals (WAS)LW821513285954568106305414.15%126878.39000000000201241.07%56277000.8101010123
13Philip BrobergCapitals (WAS)D8212021-6155821407638411.32%87178221.7312341600002161000%01849000.2400100101
14Zack MacEwenCapitals (WAS)RW8211920-13119451456411537659.57%2489210.880001150001205040.82%492217000.4501324211
15Michael SgarbossaCapitals (WAS)C8271017-3251576678218328.54%166668.13000020000361056.79%28076000.5101120101
16Andreas BorgmanCapitals (WAS)D7041216-161610481005419237.41%76116316.63202443000036010%0936000.2701002010
17Rafael Harvey-PinardCapitals (WAS)LW258614-1080372370224411.43%1234213.7101113000005035.00%40193000.8201000121
18Colin BlackwellCapitals (WAS)LW58156-237573645020342.00%1670112.09000170000480041.18%511215000.1700001000
19Logan StanleyCapitals (WAS)D43044-1582054543110200%3867715.7600006000022000%0423000.1200103000
20Tyler TuckerCapitals (WAS)D27033-34630292510770%1741715.4700001000014000%0712000.1400132000
21Jonah GadjovichCapitals (WAS)LW72021202271428.57%0486.870000000001010%120000.8300000000
22Kyle CapobiancoCapitals (WAS)D22011-36012198260%1235216.0200000000017000%027000.0600000000
23Martin KautCapitals (WAS)RW71010005550320.00%0497.120000000000000%110000.4000000001
24Cale FleuryCapitals (WAS)D14000000181611630%1321515.390000200009000%02400000000000
Statistiques d’équipe totales ou en moyenne1467254432686-77114351520662121265684114519.56%9462428516.5546821282321965336271621382248.84%5375531520400.56642362938363838
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
1Joni OrtioCapitals (WAS)62302250.9082.873553401701838745220.867305824443
2Niklas SvedbergCapitals (WAS)26131110.8863.6814202087766315000.833122458103
Statistiques d’équipe totales ou en moyenne88433360.9013.104973602572604106022428282546


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Salaire restantPlafond salarial Non Activé Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 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
Alexander HoltzCapitals (WAS)RW222002-01-23 05:01:05Yes195 Lbs6 ft0NoNoN/ANoNo2Pro & Farm894,167$0$0$No894,167$--------No--------
Alexei ProtasCapitals (WAS)C232001-01-06 05:29:17Yes225 Lbs6 ft6NoNoN/ANoNo2Pro & Farm789,167$0$0$No789,167$--------No--------
Andreas BorgmanCapitals (WAS)D281995-06-18 04:45:15Yes212 Lbs6 ft0NoNoN/ANoNo1Pro & Farm600,000$0$0$No------------------
Andrew DesjardinsCapitals (WAS)LW371986-07-27 17:11:13No196 Lbs6 ft1NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Anton BlidhCapitals (WAS)LW291995-03-14 09:14:08Yes201 Lbs6 ft0NoNoN/ANoNo1Pro & Farm575,000$0$0$No------------------
Axel Jonsson FjällbyCapitals (WAS)LW261998-02-10 04:01:54Yes189 Lbs6 ft1NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------
Beck MalenstynCapitals (WAS)LW261998-02-04 13:45:18Yes201 Lbs6 ft3NoNoN/ANoNo3Pro & Farm762,500$0$0$No762,500$762,500$-------NoNo-------
Brendan LeipsicCapitals (WAS)LW291994-05-19 17:11:13Yes182 Lbs5 ft10NoNoN/ANoNo1Pro & Farm2,000,000$0$0$No------------------
Cale FleuryCapitals (WAS)D251998-11-19 12:37:15Yes204 Lbs6 ft1NoNoN/ANoNo3Pro & Farm600,000$0$0$No600,000$600,000$-------NoNo-------
Colin BlackwellCapitals (WAS)LW311993-03-28 04:26:00Yes190 Lbs5 ft9NoNoN/ANoNo3Pro & Farm700,000$0$0$No700,000$700,000$-------NoNo-------
Dominik SimonCapitals (WAS)LW291994-08-08 07:29:33Yes190 Lbs5 ft11NoNoN/ANoNo1Pro & Farm2,000,000$0$0$No------------------
Filip ChytilCapitals (WAS)C241999-09-05 13:13:19Yes204 Lbs6 ft2NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------
Igor OzhiganovCapitals (WAS)D311992-10-13 03:56:02Yes210 Lbs6 ft2NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Ilya LyubushkinCapitals (WAS)D301994-04-06 08:31:32Yes200 Lbs6 ft2NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------
Joe SnivelyCapitals (WAS)LW281996-01-01 10:16:06Yes174 Lbs5 ft9NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------
Jonah GadjovichCapitals (WAS)LW251998-10-12 13:05:14Yes209 Lbs6 ft2NoNoN/ANoNo1Pro & Farm783,333$0$0$No------------------
Joni OrtioCapitals (WAS)G331991-04-16 23:11:14Yes187 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,250,000$0$0$No------------------
Jordan SpenceCapitals (WAS)D232001-02-24 14:18:49Yes163 Lbs5 ft10NoNoTrade2024-03-02NoNo3Pro & Farm820,000$0$0$No820,000$820,000$-------NoNo-------
Kyle CapobiancoCapitals (WAS)D261997-08-13 13:18:25Yes201 Lbs6 ft2NoNoN/ANoNo1Pro & Farm575,000$0$0$No------------------
Logan StanleyCapitals (WAS)D251998-05-26 13:08:32Yes242 Lbs6 ft7NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------
Martin KautCapitals (WAS)RW241999-10-02 12:42:37Yes190 Lbs6 ft2NoNoN/ANoNo3Pro & Farm575,000$0$0$No575,000$575,000$-------NoNo-------
Maxime LajoieCapitals (WAS)D261997-11-05 07:38:27Yes196 Lbs6 ft1NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------
Michael DipietroCapitals (WAS)G241999-06-09 10:49:43Yes200 Lbs6 ft0NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Michael SgarbossaCapitals (WAS)C311992-07-25 05:11:13Yes185 Lbs6 ft0NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------
Niklas SvedbergCapitals (WAS)G341989-09-04 11:11:14Yes179 Lbs6 ft0NoNoN/ANoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------NoNo-------
Oliver WahlstromCapitals (WAS)RW232000-06-13 12:45:28Yes204 Lbs6 ft2NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------
Philip BrobergCapitals (WAS)D222001-06-25 13:47:46Yes199 Lbs6 ft3NoNoN/ANoNo3Pro & Farm863,333$0$0$No863,333$863,333$-------NoNo-------
Rafael Harvey-PinardCapitals (WAS)LW251999-01-06 03:38:30Yes181 Lbs5 ft9NoNoTrade2024-03-02NoNo3Pro & Farm825,000$0$0$No825,000$825,000$-------NoNo-------
Ross ColtonCapitals (WAS)C271996-09-11 13:16:11Yes194 Lbs6 ft0NoNoN/ANoNo1Pro & Farm850,000$0$0$No------------------
Rudolfs BalcersCapitals (WAS)RW271997-04-08 04:53:30Yes175 Lbs5 ft11NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------
Tomas KundratekCapitals (WAS)D341989-12-26 11:11:13Yes207 Lbs6 ft2NoNoN/ANoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------NoNo-------
Tyler LewingtonCapitals (WAS)D291994-12-05 12:50:41Yes201 Lbs6 ft2NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------
Tyler TuckerCapitals (WAS)D242000-03-01 11:57:38Yes204 Lbs6 ft1NoNoN/ANoNo3Pro & Farm808,333$0$0$No808,333$808,333$-------NoNo-------
Warren FoegeleCapitals (WAS)RW281996-04-01 13:15:49Yes198 Lbs6 ft2NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------
Zack MacEwenCapitals (WAS)RW271996-07-08 04:15:59Yes205 Lbs6 ft3NoNoN/ANoNo3Pro & Farm700,000$0$0$No700,000$700,000$-------NoNo-------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3527.29197 Lbs6 ft12.00877,024$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dominik SimonFilip ChytilWarren Foegele35122
2Brendan LeipsicRoss ColtonOliver Wahlstrom35122
3Rafael Harvey-PinardAlexei ProtasRudolfs Balcers25122
4Axel Jonsson FjällbyMichael SgarbossaZack MacEwen5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinTomas Kundratek35122
2Maxime LajoiePhilip Broberg35122
3Andreas BorgmanKyle Capobianco30122
4Ilya LyubushkinTomas Kundratek0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dominik SimonFilip ChytilWarren Foegele60122
2Brendan LeipsicRoss ColtonOliver Wahlstrom40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinTomas Kundratek60122
2Maxime LajoiePhilip Broberg40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Filip ChytilRoss Colton60122
2Dominik SimonBrendan Leipsic40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinTomas Kundratek60122
2Maxime LajoiePhilip Broberg40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Filip Chytil60122Ilya LyubushkinTomas Kundratek60122
2Ross Colton40122Maxime LajoiePhilip Broberg40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Filip ChytilRoss Colton60122
2Dominik SimonBrendan Leipsic40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ilya LyubushkinTomas Kundratek60122
2Maxime LajoiePhilip Broberg40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dominik SimonFilip ChytilWarren FoegeleIlya LyubushkinTomas Kundratek
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dominik SimonFilip ChytilWarren FoegeleIlya LyubushkinTomas Kundratek
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Rafael Harvey-Pinard, Rudolfs Balcers, Zack MacEwenRafael Harvey-Pinard, Rudolfs BalcersZack MacEwen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Andreas Borgman, Kyle Capobianco, Maxime LajoieAndreas BorgmanKyle Capobianco, Maxime Lajoie
Tirs de pénalité
Filip Chytil, Ross Colton, Dominik Simon, Brendan Leipsic, Warren Foegele
Gardien
#1 : Niklas Svedberg, #2 : Joni Ortio
Lignes d’attaque personnalisées en prolongation
Filip Chytil, Ross Colton, Dominik Simon, Brendan Leipsic, Warren Foegele, Oliver Wahlstrom, Oliver Wahlstrom, Rafael Harvey-Pinard, Rudolfs Balcers, Zack MacEwen, Alexei Protas
Lignes de défense personnalisées en prolongation
Ilya Lyubushkin, Tomas Kundratek, Maxime Lajoie, Philip Broberg, Andreas Borgman


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
1Avalanche311000101394100000105412110000085340.66713243700559795139381989792065952615706350.00%5260.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
2Blackhawks32100000912-31100000032121100000610-440.6679142300559795139381989792065994442763133.33%6183.33%11024206549.59%985203648.38%620123650.16%1728100718467421405691
3Blues32100000862220000007341010000013-240.6678142200559795131108198979206510929865300.00%40100.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
4Bruins3110001013121100000104312110000099040.6671319320055979513101819897920659438617815213.33%80100.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
5Canadiens32100000972110000004132110000056-140.6679152400559795131048198979206510130437310330.00%90100.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
6Canucks31200000610-41010000035-22110000035-220.3336111700559795131048198979206593431573300.00%50100.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
7Devils512010011819-131100001131302010100056-150.5001831490055979513164819897920651524114616431516.13%24483.33%01024206549.59%985203648.38%620123650.16%1728100718467421405691
8Ducks4110002014140311000101112-11000001032160.7501420340055979513127819897920651374747100300.00%11372.73%01024206549.59%985203648.38%620123650.16%1728100718467421405691
9Flames31101000972201010005501100000042240.66791625005597951311081989792065933533587228.57%4175.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
10Flyers512011001113-22010100045-13110010078-150.50011182900559795131418198979206516755681362328.70%18383.33%01024206549.59%985203648.38%620123650.16%1728100718467421405691
11Islanders623001001825-7412001001017-72110000088050.4171829470055979513205819897920651916210614627622.22%33875.76%01024206549.59%985203648.38%620123650.16%1728100718467421405691
12Kings3100100112111100010006512100000166050.83312223400559795139981989792065924112727228.57%6183.33%01024206549.59%985203648.38%620123650.16%1728100718467421405691
13Maple Leafs3110000178-1110000003212010000146-230.5007916005597951310381989792065903023671000.00%9188.89%11024206549.59%985203648.38%620123650.16%1728100718467421405691
14Oilers3120000059-42110000045-11010000014-320.3335914005597951310581989792065104287753133.33%10100.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
15Penguins51300010161513110001012752020000048-440.4001627431055979513155819897920651556212814116637.50%24483.33%01024206549.59%985203648.38%620123650.16%1728100718467421405691
16Predators3110100014113201010009901100000052340.6671425390055979513110819897920651054237703133.33%6183.33%01024206549.59%985203648.38%620123650.16%1728100718467421405691
17Rangers53200000151412110000055032100000109160.6001528430055979513146819897920651245320513828517.86%20195.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
18Red Wings31200000101001010000023-12110000087120.333101828005597951385819897920651003220698225.00%10190.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
19Sabres302010001012-22010100078-11010000034-120.33310192910559795139381989792065934541761000.00%13376.92%01024206549.59%985203648.38%620123650.16%1728100718467421405691
20Senateurs321000001213-11010000015-422000000118340.66712203200559795139081989792065973655768112.50%10280.00%11024206549.59%985203648.38%620123650.16%1728100718467421405691
21Sharks321000001073211000007611100000031240.667101626005597951310681989792065923315674250.00%50100.00%01024206549.59%985203648.38%620123650.16%1728100718467421405691
22Stars311010001192201010007701100000042240.667111627005597951310881989792065100476759111.11%3166.67%01024206549.59%985203648.38%620123650.16%1728100718467421405691
23Wild42100001910-1110000004313110000157-250.6259152400559795131088198979206512348161107114.29%8187.50%01024206549.59%985203648.38%620123650.16%1728100718467421405691
Total82313307254259263-441131606141136135141181701113123128-5920.56125943569420559795132660819897920652606947114920752444618.85%2423884.30%31024206549.59%985203648.38%620123650.16%1728100718467421405691
_Since Last GM Reset82313307254259263-441131606141136135141181701113123128-5920.56125943569420559795132660819897920652606947114920752444618.85%2423884.30%31024206549.59%985203648.38%620123650.16%1728100718467421405691
_Vs Conference44152003222139148-92169021216569-423911011017479-5440.5001392333722055979513138781989792065136448489611641863217.20%1782784.83%21024206549.59%985203648.38%620123650.16%1728100718467421405691
_Vs Division26812022117886-81446011114447-31246011003439-5250.481781332111055979513811819897920657892736537251252419.20%1192083.19%01024206549.59%985203648.38%620123650.16%1728100718467421405691

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8292W1259435694266026069471149207520
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8231337254259263
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4113166141136135
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4118171113123128
Derniers 10 matchs
WLOTWOTL SOWSOL
720001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2444618.85%2423884.30%3
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
8198979206555979513
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
1024206549.59%985203648.38%620123650.16%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1728100718467421405691


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
13Islanders3Capitals5BWSommaire du match
212Capitals2Flyers3ALXSommaire du match
531Devils7Capitals3BLSommaire du match
744Penguins3Capitals8BWR5Sommaire du match
1369Capitals2Wild3ALXXSommaire du match
1476Ducks5Capitals1BLSommaire du match
1894Stars5Capitals4BLSommaire du match
1997Capitals6Rangers5AWSommaire du match
22115Capitals3Devils5ALSommaire du match
24125Islanders5Capitals0BLSommaire du match
26140Capitals1Rangers2ALSommaire du match
28148Predators2Capitals3BWXSommaire du match
30157Capitals3Bruins5ALSommaire du match
32168Capitals5Islanders4AWSommaire du match
33178Ducks2Capitals4BWSommaire du match
36194Oilers2Capitals3BWSommaire du match
39206Capitals6Bruins4AWSommaire du match
43222Wild3Capitals4BWSommaire du match
45236Capitals3Ducks2AWXXSommaire du match
47245Maple Leafs2Capitals3BWSommaire du match
49253Capitals2Devils1AWXSommaire du match
51268Ducks5Capitals6BWXXSommaire du match
53281Capitals5Predators2AWSommaire du match
55291Devils2Capitals7BWSommaire du match
56299Capitals3Avalanche4ALSommaire du match
59315Devils4Capitals3BLXXSommaire du match
61323Capitals5Avalanche1AWSommaire du match
63336Capitals3Rangers2AWSommaire du match
65345Predators7Capitals6BLSommaire du match
67355Capitals1Blues3ALSommaire du match
69367Capitals6Senateurs4AWSommaire du match
71375Stars2Capitals3BWXSommaire du match
74392Capitals4Flames2AWSommaire du match
76401Canucks5Capitals3BLSommaire du match
80416Sabres3Capitals4BWXSommaire du match
84436Senateurs5Capitals1BLSommaire du match
89459Bruins3Capitals4BWXXSommaire du match
92474Capitals5Senateurs4AWSommaire du match
93483Flames3Capitals2BLSommaire du match
96495Capitals3Penguins5ALR5Sommaire du match
98504Capitals1Flyers3ALSommaire du match
99511Flames2Capitals3BWXSommaire du match
102528Capitals4Flyers2AWSommaire du match
103534Avalanche4Capitals5BWXXSommaire du match
108555Islanders4Capitals3BLXSommaire du match
110563Capitals3Canucks1AWSommaire du match
112578Capitals3Sharks1AWSommaire du match
114583Islanders5Capitals2BLSommaire du match
116595Capitals3Sabres4ALSommaire du match
118603Capitals2Blackhawks8ALSommaire du match
119610Red Wings3Capitals2BLR2Sommaire du match
122629Oilers3Capitals1BLSommaire du match
124640Capitals1Wild3ALSommaire du match
127655Canadiens1Capitals4BWR2Sommaire du match
129662Capitals3Islanders4ALSommaire du match
131675Capitals4Blackhawks2AWSommaire du match
133681Penguins2Capitals1BLR5Sommaire du match
136699Capitals2Canadiens4ALR2Sommaire du match
138705Sabres5Capitals3BLSommaire du match
141724Capitals1Maple Leafs2ALSommaire du match
142730Rangers2Capitals4BWSommaire du match
145743Capitals0Canucks4ALSommaire du match
147753Blackhawks2Capitals3BWSommaire du match
150772Capitals3Maple Leafs4ALXXSommaire du match
151779Rangers3Capitals1BLSommaire du match
153792Capitals3Canadiens2AWR2Sommaire du match
155802Sharks4Capitals7BWSommaire du match
158820Capitals4Stars2AWSommaire du match
159826Capitals1Penguins3ALR5Sommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
161833Flyers2Capitals3BWXSommaire du match
164850Sharks2Capitals0BLSommaire du match
166863Capitals4Red Wings5ALR2Sommaire du match
168872Capitals3Kings2AWSommaire du match
169877Capitals2Wild1AWSommaire du match
170884Kings5Capitals6BWXSommaire du match
172896Capitals1Oilers4ALSommaire du match
174908Blues1Capitals2BWSommaire du match
175918Capitals3Kings4ALXXSommaire du match
179935Penguins2Capitals3BWXXR5Sommaire du match
180941Capitals4Red Wings2AWR2Sommaire du match
184957Flyers3Capitals1BLSommaire du match
190974Blues2Capitals5BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance59,06439,626
Assistance PCT72.03%96.65%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2407 - 80.24% 120,134$4,925,514$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
3,696,366$ 3,069,583$ 1,463,667$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 2,946,368$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 19,791$ 0$




Capitals 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

Capitals 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

Capitals 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

Capitals 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

Capitals 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