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Seattle
GP: 82 | W: 59 | L: 18 | OTL: 5 | P: 123
GF: 222 | GA: 141 | PP%: 13.27% | PK%: 89.47%
DG: Yvon Bergeron | Morale : 50 | Moyenne d’équipe : 64
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Centre de jeu
Seattle
59-18-5, 123pts
4
FINAL
3 Oceanics
56-21-5, 117pts
Team Stats
W3SéquenceW1
33-5-3Fiche domicile25-12-4
26-13-2Fiche domicile31-9-1
8-1-1Derniers 10 matchs6-2-2
2.71Buts par match 2.70
1.72Buts contre par match 1.55
13.27%Pourcentage en avantage numérique16.80%
89.47%Pourcentage en désavantage numérique88.65%
Seattle
59-18-5, 123pts
4
FINAL
1 Minnesota
34-45-3, 71pts
Team Stats
W3SéquenceL1
33-5-3Fiche domicile21-19-1
26-13-2Fiche domicile13-26-2
8-1-1Derniers 10 matchs3-6-1
2.71Buts par match 2.44
1.72Buts contre par match 2.72
13.27%Pourcentage en avantage numérique11.02%
89.47%Pourcentage en désavantage numérique80.63%
Meneurs d'équipe
Buts
Rem Pitlick
38
Passes
Rem Pitlick
46
Points
Rem Pitlick
84
Plus/Moins
Rem Pitlick
52
Victoires
Alex Nedeljkovic
59
Pourcentage d’arrêts
Ukko-Pekka Luukkonen
0.923

Statistiques d’équipe
Buts pour
222
2.71 GFG
Tirs pour
1675
20.43 Avg
Pourcentage en avantage numérique
13.3%
28 GF
Début de zone offensive
40.3%
Buts contre
141
1.72 GAA
Tirs contre
1388
16.93 Avg
Pourcentage en désavantage numérique
89.5%%
28 GA
Début de la zone défensive
38.0%
Informations de l'équipe

Directeur généralYvon Bergeron
DivisionMid-Ouest
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité6,000
Assistance5,751
Billets de saison600


Informations de la formation

Équipe Pro27
Équipe Mineure20
Limite contact 47 / 50
Espoirs29


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire moyen
1Rem PitlickXXX100.006647777677838074567169677369590507002512,000,000$
2Jansen HarkinsXX100.00694782748180757045636466696454050670252750,000$
3Kale ClagueX100.006147697478847269406561656864540506602431,700,000$
4Alex Barre-BouletXX100.00624564726066666964686168685450050640252759,258$
5Andreas JohnssonXX100.006443676966717067456760656662530506402712,000,000$
6Henrik BorgstromX100.00624374657070706349605758615853050610252900,000$
7Nolan Foote (R)X100.00655068696763626343616062645050050610211894,167$
8Radim ZohornaXXX100.00685064607266656157605664595550050610262792,500$
9Arshdeep Bains (R)X100.00624068686261626242625861625050050600213816,667$
10Roby Jarventie (R)X100.00604565666455546243605851625050050580203894,167$
11Haydn FleuryX100.006547787286837669406161706874640506902621,000,000$
12Jakub ZborilX100.00664380748184736740636169676959050690252750,000$
13Travis DermottX100.00604378748283756840626269687464050690252800,000$
14Ryan MurrayX100.005843777182837667406360666684740506802921,000,000$
15Jeremy DaviesX100.00594757726166656540596068655450050630252750,000$
16Simon Lundmark (R)X100.00644572686662626240585466625050050620213850,833$
17Olli JuoleviX100.00554371676767626140595459615550050600241750,000$
Rayé
1Brett MurrayX100.00686064627365656443626160625250050610242775,000$
2Fredrik KarlstromX100.00614572656565646256595658615350050600242700,000$
3Emil Heineman (R)X100.00624068666358575840545559595050050580203897,500$
4Ilya Usau (R)X100.00614069666260615951585459595050050580213897,500$
5Zach BogosianX100.0074556471848390714064637168908005072N03211,000,000$
6Brendan GuhleX100.00717376777352564425323863375959050580252650,000$
7Markus NutivaaraX100.00524365616565615640535353567562050580281675,000$
MOYENNE D’ÉQUIPE100.0063477069717067644460586363615605063
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPÂgeContratSalaire moyen
1Alex Nedeljkovic100.00838281838281767980827977700507402622,800,000$
2Ukko-Pekka Luukkonen100.00777677878278757676787557520507102342,200,000$
Rayé
1Spencer Martin100.0079787976817673737580747165050700271750,000$
MOYENNE D’ÉQUIPE100.008079798282787576778076686205072
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
1Rem PitlickSeattle (SEA)C/LW/RW81384684524151122072736517613.92%12195924.1957123718300022577258.58%196500030.864100011346
2Jansen HarkinsSeattle (SEA)C/LW81303060493001051151846411316.30%14176721.823472118200082679148.76%12100110.686100006113
3Alex Barre-BouletSeattle (SEA)LW/RW81282553212401141201884711714.89%6148418.32391225170000008156.25%8000010.7101000833
4Ryan MurraySeattle (SEA)D8113405341220966468204219.12%54180822.33459291790110222500%000000.5900000364
5Andreas JohnssonSeattle (SEA)LW/RW812030505034010291134378814.93%7156019.260441517801111261354.93%7100000.6425000555
6Kale ClagueSeattle (SEA)LW8120274723275741331644613312.20%8165220.404592617710131326254.65%17200000.5715001543
7Travis DermottSeattle (SEA)D815374240320126817031697.14%70190923.57156381870001223300%000000.4400000239
8Jeremy DaviesSeattle (SEA)D815323723520166625723388.77%44154019.01268261380000160200%000000.4800000122
9Henrik BorgstromSeattle (SEA)C81101929132407412686184811.63%11136616.871128900000632154.21%114000000.4200000123
10Radim ZohornaSeattle (SEA)C/LW/RW8181725146151171078426619.52%3135716.7602210900001571060.26%109700000.3700001021
11Nolan FooteSeattle (SEA)LW81915247360779110038949.00%3113714.040002140000152156.36%5500000.4200000032
12Olli JuoleviSeattle (SEA)D812141653806531259118.00%40114414.1300029000063100%000000.2800000103
13Roby JarventieSeattle (SEA)LW7641115-224064445022528.00%095612.580226430000130048.78%4100000.3100000111
14Simon LundmarkSeattle (SEA)D814111534151095327152014.81%47137516.982021170000091200%000000.2200000002
15Brett MurraySeattle (SEA)LW57951455010734876166311.84%288815.5900000000001056.76%3700000.3200001201
16Haydn FleurySeattle (SEA)D151101114402613138137.69%630620.46101733000040000%000000.7200000010
17Jakub ZborilSeattle (SEA)D1529111580231421889.52%1236624.44112832000039000%000000.6000000022
18Arshdeep BainsSeattle (SEA)LW78369824056373914177.69%147709.870001140000221036.59%4100000.2300000002
19Fredrik KarlstromSeattle (SEA)C56213-1201020123716.67%42223.9700000000001060.87%18400000.2700000001
20Emil HeinemanSeattle (SEA)LW20000-220450220%2703.51000080000160039.13%230000000000000
Statistiques d’équipe totales ou en moyenne137021338559837857630159314621671512117212.75%3592364317.262751782721806123161817521157.19%502700150.511331004484953
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 NedeljkovicSeattle (SEA)81591750.9021.63487301613213500100.82434810670
2Ukko-Pekka LuukkonenSeattle (SEA)20000.9231.50400011300000081000
Statistiques d’équipe totales ou en moyenne83591750.9021.6249140161331363010348181670


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Recrue Poids Taille Non-échange Disponible pour échange Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Lien
Alex Barre-BouletSeattle (SEA)LW/RW251997-05-21No181 Lbs5 ft10NoNoYesYes2Pro & Farm759,258$0$0$No759,258$Lien
Alex NedeljkovicSeattle (SEA)G261996-01-07No208 Lbs6 ft0NoNoYesYes2Pro & Farm2,800,000$0$0$No2,800,000$Lien
Andreas Johnsson (contrat à 1 volet)Seattle (SEA)LW/RW271994-11-21No194 Lbs5 ft10NoNoYesYes1Pro & Farm2,000,000$1,100,000$0$NoLien
Arshdeep BainsSeattle (SEA)LW212001-01-09Yes183 Lbs6 ft1NoNoNoNo3Pro & Farm816,667$0$0$No816,667$816,667$
Brendan GuhleSeattle (SEA)D251997-07-29No197 Lbs6 ft2NoNoYesYes2Pro & Farm650,000$0$0$No650,000$Lien
Brett MurraySeattle (SEA)LW241998-07-20No227 Lbs6 ft5NoNoYesYes2Pro & Farm775,000$0$0$No775,000$Lien
Emil HeinemanSeattle (SEA)LW202001-11-16Yes185 Lbs6 ft1NoNoNoNo3Pro & Farm897,500$0$0$No897,500$897,500$
Fredrik KarlstromSeattle (SEA)C241998-01-12No194 Lbs6 ft3NoNoYesYes2Pro & Farm700,000$0$0$No700,000$Lien
Haydn FleurySeattle (SEA)D261996-07-08No208 Lbs6 ft4NoNoYesYes2Pro & Farm1,000,000$0$0$No1,000,000$Lien
Henrik BorgstromSeattle (SEA)C251997-08-06No198 Lbs6 ft3NoNoYesYes2Pro & Farm900,000$0$0$No900,000$Lien
Ilya UsauSeattle (SEA)C212001-08-03Yes183 Lbs6 ft1NoNoNoNo3Pro & Farm897,500$0$0$No897,500$897,500$
Jakub ZborilSeattle (SEA)D251997-02-21No201 Lbs6 ft1NoNoYesYes2Pro & Farm750,000$0$0$No750,000$Lien
Jansen HarkinsSeattle (SEA)C/LW251997-05-23No197 Lbs6 ft2NoNoYesYes2Pro & Farm750,000$0$0$No750,000$Lien
Jeremy DaviesSeattle (SEA)D251996-12-04No181 Lbs5 ft11NoNoYesYes2Pro & Farm750,000$0$0$No750,000$Lien
Kale ClagueSeattle (SEA)LW241998-06-05No190 Lbs6 ft0NoNoYesYes3Pro & Farm1,700,000$0$0$No1,700,000$1,700,000$Lien
Markus Nutivaara (contrat à 1 volet)Seattle (SEA)D281994-06-06No187 Lbs6 ft1NoNoYesYes1Pro & Farm675,000$0$0$NoLien
Nolan FooteSeattle (SEA)LW212000-11-29Yes196 Lbs6 ft3NoNoNoNo1Pro & Farm894,167$0$0$NoLien
Olli JuoleviSeattle (SEA)D241998-05-05No183 Lbs6 ft2NoNoYesYes1Pro & Farm750,000$0$0$NoLien
Radim ZohornaSeattle (SEA)C/LW/RW261996-04-29No220 Lbs6 ft6NoNoYesYes2Pro & Farm792,500$0$0$No792,500$Lien
Rem PitlickSeattle (SEA)C/LW/RW251997-04-02No186 Lbs5 ft11NoNoYesYes1Pro & Farm2,000,000$0$0$NoLien
Roby JarventieSeattle (SEA)LW202002-08-08Yes183 Lbs6 ft2NoNoNoNo3Pro & Farm894,167$0$0$No894,167$894,167$Lien
Ryan Murray (contrat à 1 volet)Seattle (SEA)D291993-09-27No206 Lbs6 ft1NoNoYesYes2Pro & Farm1,000,000$100,000$0$No1,000,000$Lien
Simon LundmarkSeattle (SEA)D212000-10-08Yes201 Lbs6 ft2NoNoNoNo3Pro & Farm850,833$0$0$No850,833$850,833$Lien
Spencer Martin (contrat à 1 volet)Seattle (SEA)G271995-06-08No191 Lbs6 ft3NoNoYesYes1Pro & Farm750,000$0$0$NoLien
Travis DermottSeattle (SEA)D251996-12-22No202 Lbs6 ft0NoNoYesYes2Pro & Farm800,000$0$0$No800,000$Lien
Ukko-Pekka LuukkonenSeattle (SEA)G231999-03-09No217 Lbs6 ft5NoNoNoNo4Pro & Farm2,200,000$0$0$No2,200,000$2,200,000$2,200,000$Lien
Zach Bogosian (contrat à 1 volet)Seattle (SEA)D321990-07-15No222 Lbs6 ft2YesNoYesYes1Pro & Farm1,000,000$100,000$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2724.59197 Lbs6 ft22.041,064,911$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jansen HarkinsRem PitlickAndreas Johnsson40122
2Kale ClagueRadim ZohornaAlex Barre-Boulet30122
3Nolan FooteHenrik BorgstromArshdeep Bains20122
4Arshdeep BainsRem PitlickJansen Harkins10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilHaydn Fleury40122
2Travis DermottRyan Murray30122
3Jeremy DaviesSimon Lundmark20122
4Olli JuoleviJakub Zboril10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jansen HarkinsRem PitlickAndreas Johnsson60122
2Kale ClagueRadim ZohornaAlex Barre-Boulet40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilHaydn Fleury60122
2Travis DermottRyan Murray40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Rem PitlickJansen Harkins60122
2Kale ClagueAndreas Johnsson40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilHaydn Fleury60122
2Travis DermottRyan Murray40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Rem Pitlick60122Jakub ZborilHaydn Fleury60122
2Jansen Harkins40122Travis DermottRyan Murray40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Rem PitlickJansen Harkins60122
2Kale ClagueAndreas Johnsson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilHaydn Fleury60122
2Travis DermottRyan Murray40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jansen HarkinsRem PitlickAndreas JohnssonJakub ZborilHaydn Fleury
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jansen HarkinsRem PitlickAndreas JohnssonJakub ZborilHaydn Fleury
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Roby Jarventie, Nolan Foote, Henrik BorgstromRoby Jarventie, Nolan FooteHenrik Borgstrom
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jeremy Davies, Simon Lundmark, Olli JuoleviJeremy DaviesSimon Lundmark, Olli Juolevi
Tirs de pénalité
Rem Pitlick, Jansen Harkins, Kale Clague, Andreas Johnsson, Alex Barre-Boulet
Gardien
#1 : Alex Nedeljkovic, #2 : Ukko-Pekka Luukkonen


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
1Admirals431000001394220000009452110000045-160.750132538009966491484594551521415014226413215.38%10370.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
2Baby Hawks31100010761210000105321010000023-140.66771118009966491454594551521414216226011327.27%110100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
3Bears22000000734110000004131100000032141.00071320009966491447594551521412521035200.00%5260.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
4Bruins2010001035-2100000103211010000003-320.5003470099664914365945515214130122549300.00%6266.67%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
5Cabaret Lady Mary Ann21000010743110000003121000001043141.0007121900996649144259455152141281112297228.57%60100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
6Caroline22000000303110000001011100000020241.0003690299664914255945515214128819468112.50%70100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
7Chiefs31100010541100000103212110000022040.667571201996649145359455152141421224541100.00%110100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
8Chill3300000013211220000009181100000041361.0001324370199664914685945515214150181768500.00%6183.33%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
9Comets32000001624210000014221100000020250.833612180199664914635945515214137101563600.00%60100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
10Cougars2010000148-41010000025-31000000123-110.25047110099664914455945515214153152433200.00%11190.91%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
11Crunch22000000404110000003031100000010141.00047110299664914395945515214134118494250.00%40100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
12Heat4400000016214220000009182200000071681.000162844029966491410059455152141532130775240.00%130100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
13Jayhawks3300000014591100000043122000000102861.00014274100996649149859455152141642318627114.29%80100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
14Las Vegas42101000660210010004132110000025-360.750612180299664914755945515214173163070500.00%15193.33%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
15Manchots21100000532110000005141010000002-220.50059140099664914435945515214134814408337.50%70100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
16Marlies22000000716110000003121100000040441.0007142101996649142859455152141401020407228.57%9188.89%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
17Minnesota33000000927220000005141100000041361.000914230199664914735945515214149918768112.50%90100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
18Monarchs320000101349110000004132100001093661.00013223500996649147259455152141491222556233.33%10190.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
19Monsters22000000633110000003121100000032141.00061117009966491433594551521412861741400.00%5180.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
20Monsters3110010046-2210001003301010000013-230.5004711009966491445594551521414812185713215.38%9277.78%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
21Oceanics3120000057-21010000012-12110000045-120.33358130099664914635945515214169152457700.00%12191.67%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
22Oil Kings440000001697220000009542200000074381.00016294500996649148959455152141572230839111.11%13376.92%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
23Phantoms21100000440110000003211010000012-120.50047110099664914395945515214139152636300.00%10190.00%11167207056.38%1101195456.35%636111457.09%2142153118045651029533
24Rocket21000001550110000004311000000112-130.75051015009966491443594551521413091046400.00%5180.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
25Sags42000020844210000103122100001053281.0008111902996649147459455152141751826641200.00%12191.67%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
26Senators2110000034-11010000003-31100000031220.5003690099664914375945515214134912287114.29%6183.33%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
27Sound Tigers20200000510-51010000046-21010000014-300.00059140099664914275945515214147924396233.33%12375.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
28Spiders2020000028-61010000013-21010000015-400.0002350099664914335945515214135619411000.00%7185.71%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
29Stars311001006601000010023-12110000043130.500610160099664914545945515214163182065800.00%10190.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
30Thunder220000001138110000007251100000041341.0001120310099664914575945515214135910486116.67%50100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
31Wolf Pack2110000056-1110000003211010000024-220.50059140099664914365945515214147151239400.00%60100.00%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
Total825118012732221418141285012411236657412313000329975241230.75022239461601599664914167559455152141138839159816142112813.27%2662889.47%11167207056.38%1101195456.35%636111457.09%2142153118045651029533
_Since Last GM Reset825118012732221418141285012411236657412313000329975241230.75022239461601599664914167559455152141138839159816142112813.27%2662889.47%11167207056.38%1101195456.35%636111457.09%2142153118045651029533
_Vs Conference4328601233112654722151012216133282113500012513219690.80211219931101199664914898594551521417012132988701081513.89%138993.48%01167207056.38%1101195456.35%636111457.09%2142153118045651029533
_Vs Division267401021783642134101020421527133300001362115210.4047813921707996649145575945515214139411317547656712.50%79988.61%01167207056.38%1101195456.35%636111457.09%2142153118045651029533

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82123W3222394616167513883915981614015
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8251181273222141
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
41285124112366
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
41231300329975
Derniers 10 matchs
WLOTWOTL SOWSOL
810100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2112813.27%2662889.47%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
5945515214199664914
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
1167207056.38%1101195456.35%636111457.09%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2142153118045651029533


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
1 - 2023-10-103Seattle1Las Vegas5ALSommaire du match
3 - 2023-10-1215Seattle4Chill1AWSommaire du match
5 - 2023-10-1428Seattle0Chiefs2ALSommaire du match
8 - 2023-10-1746Monsters2Seattle3BWSommaire du match
10 - 2023-10-1960Caroline0Seattle1BWSommaire du match
12 - 2023-10-2177Wolf Pack2Seattle3BWSommaire du match
15 - 2023-10-2491Seattle2Cougars3ALXXSommaire du match
17 - 2023-10-26101Seattle2Caroline0AWSommaire du match
19 - 2023-10-28118Seattle4Cabaret Lady Mary Ann3AWXXSommaire du match
21 - 2023-10-30133Seattle4Thunder1AWSommaire du match
24 - 2023-11-02154Chill1Seattle4BWSommaire du match
26 - 2023-11-04170Heat1Seattle3BWSommaire du match
29 - 2023-11-07185Seattle3Jayhawks1AWSommaire du match
31 - 2023-11-09201Seattle1Monsters3ALSommaire du match
33 - 2023-11-11220Oil Kings3Seattle4BWSommaire du match
35 - 2023-11-13228Monsters1Seattle0BLXSommaire du match
37 - 2023-11-15239Seattle3Oil Kings2AWSommaire du match
38 - 2023-11-16248Sound Tigers6Seattle4BLSommaire du match
40 - 2023-11-18265Seattle2Comets0AWSommaire du match
42 - 2023-11-20277Heat0Seattle6BWSommaire du match
44 - 2023-11-22291Sags0Seattle1BWXXSommaire du match
46 - 2023-11-24307Comets1Seattle0BLXXSommaire du match
50 - 2023-11-28333Seattle2Baby Hawks3ALSommaire du match
52 - 2023-11-30346Seattle4Marlies0AWSommaire du match
54 - 2023-12-02362Seattle3Senators1AWSommaire du match
56 - 2023-12-04377Seattle1Rocket2ALXXSommaire du match
59 - 2023-12-07403Spiders3Seattle1BLSommaire du match
61 - 2023-12-09418Thunder2Seattle7BWSommaire du match
62 - 2023-12-10426Minnesota1Seattle3BWSommaire du match
64 - 2023-12-12437Cabaret Lady Mary Ann1Seattle3BWSommaire du match
66 - 2023-12-14453Baby Hawks1Seattle2BWXXSommaire du match
68 - 2023-12-16471Monarchs1Seattle4BWSommaire du match
70 - 2023-12-18482Seattle3Stars1AWSommaire du match
72 - 2023-12-20497Seattle6Monarchs1AWSommaire du match
75 - 2023-12-23523Seattle2Admirals4ALSommaire du match
79 - 2023-12-27539Seattle4Heat1AWSommaire du match
81 - 2023-12-29554Phantoms2Seattle3BWSommaire du match
84 - 2024-01-01573Las Vegas0Seattle1BWXSommaire du match
87 - 2024-01-04598Senators3Seattle0BLSommaire du match
92 - 2024-01-09625Seattle1Crunch0AWSommaire du match
94 - 2024-01-11645Seattle3Bears2AWSommaire du match
96 - 2024-01-13659Seattle3Monsters2AWSommaire du match
98 - 2024-01-15677Seattle0Manchots2ALSommaire du match
99 - 2024-01-16681Seattle2Wolf Pack4ALSommaire du match
101 - 2024-01-18698Seattle4Oil Kings2AWSommaire du match
104 - 2024-01-21723Marlies1Seattle3BWSommaire du match
107 - 2024-01-24743Baby Hawks2Seattle3BWSommaire du match
109 - 2024-01-26758Chiefs2Seattle3BWXXSommaire du match
111 - 2024-01-28774Monsters1Seattle3BWSommaire du match
113 - 2024-01-30777Seattle1Sags0AWSommaire du match
124 - 2024-02-10814Seattle1Phantoms2ALSommaire du match
126 - 2024-02-12819Seattle1Spiders5ALSommaire du match
127 - 2024-02-13829Seattle1Sound Tigers4ALSommaire du match
129 - 2024-02-15837Seattle0Bruins3ALSommaire du match
133 - 2024-02-19870Cougars5Seattle2BLSommaire du match
136 - 2024-02-22897Comets1Seattle4BWSommaire du match
138 - 2024-02-24912Minnesota0Seattle2BWSommaire du match
140 - 2024-02-26926Bruins2Seattle3BWXXSommaire du match
143 - 2024-02-29950Manchots1Seattle5BWSommaire du match
145 - 2024-03-02958Oil Kings2Seattle5BWSommaire du match
147 - 2024-03-04980Seattle3Heat0AWSommaire du match
148 - 2024-03-05986Seattle0Oceanics2ALSommaire du match
151 - 2024-03-081008Oceanics2Seattle1BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
155 - 2024-03-121040Las Vegas1Seattle3BWSommaire du match
157 - 2024-03-141056Bears1Seattle4BWSommaire du match
159 - 2024-03-161070Chill0Seattle5BWSommaire du match
161 - 2024-03-181081Crunch0Seattle3BWSommaire du match
164 - 2024-03-211107Seattle1Las Vegas0AWSommaire du match
165 - 2024-03-221112Seattle7Jayhawks1AWSommaire du match
167 - 2024-03-241132Rocket3Seattle4BWSommaire du match
169 - 2024-03-261146Admirals2Seattle4BWSommaire du match
171 - 2024-03-281162Admirals2Seattle5BWSommaire du match
173 - 2024-03-301178Stars3Seattle2BLXSommaire du match
175 - 2024-04-011188Seattle4Sags3AWXXSommaire du match
177 - 2024-04-031201Seattle3Monarchs2AWXXSommaire du match
179 - 2024-04-051215Seattle2Admirals1AWSommaire du match
183 - 2024-04-091250Jayhawks3Seattle4BWSommaire du match
185 - 2024-04-111263Sags1Seattle2BWSommaire du match
187 - 2024-04-131271Seattle1Stars2ALSommaire du match
188 - 2024-04-141283Seattle2Chiefs0AWSommaire du match
190 - 2024-04-161300Seattle4Oceanics3AWSommaire du match
192 - 2024-04-181307Seattle4Minnesota1AWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité40002000
Prix des billets3515
Assistance156,67879,093
Assistance PCT95.54%96.45%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 5751 - 95.84% 195,223$8,004,150$6000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,544,250$ 3,332,760$ 3,332,760$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
17,358$ 2,544,250$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 17,358$ 0$




Seattle 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

Seattle 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

Seattle 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

Seattle 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

Seattle 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