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Seattle
GP: 10 | W: 4 | L: 6
GF: 35 | GA: 40 | PP%: 10.34% | PK%: 80.00%
DG: Yvon Bergeron | Morale : 50 | Moyenne d’équipe : 61
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Centre de jeu
Seattle
4-6-0, 8pts
0
FINAL
4 Comets
11-7-0, 22pts
Team Stats
L4StreakOTL1
2-3-0Home Record6-2-0
2-3-0Away Record5-5-0
4-6-0Last 10 Games6-3-1
3.50Buts par match 3.67
4.00Buts contre par match 2.78
10.34%Pourcentage en avantage numérique22.64%
80.00%Pourcentage en désavantage numérique87.50%
Seattle
4-6-0, 8pts
3
FINAL
5 Comets
11-7-0, 22pts
Team Stats
L4StreakOTL1
2-3-0Home Record6-2-0
2-3-0Away Record5-5-0
4-6-0Last 10 Games6-3-1
3.50Buts par match 3.67
4.00Buts contre par match 2.78
10.34%Pourcentage en avantage numérique22.64%
80.00%Pourcentage en désavantage numérique87.50%
Meneurs d'équipe
Buts
Nolan Foote
6
Passes
Nolan Foote
8
Points
Nolan Foote
14
Plus/Moins
Simon Lundmark
11
Victoires
Alex Nedeljkovic
1
Pourcentage d’arrêts
Alex Nedeljkovic
0.906

Statistiques d’équipe
Buts pour
35
3.50 GFG
Tirs pour
398
39.80 Avg
Pourcentage en avantage numérique
10.3%
3 GF
Début de zone offensive
41.0%
Buts contre
40
4.00 GAA
Tirs contre
420
42.00 Avg
Pourcentage en désavantage numérique
80.0%%
10 GA
Début de la zone défensive
40.4%
Informations de l'équipe

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


Informations de l’aréna

Capacité6,000
Assistance6,000
Billets de saison600


Informations de la formation

Équipe Pro20
Équipe Mineure20
Limite contact 40 / 50
Espoirs18


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
1William CarrierX100.009046847979618362446366662565680506502621,100,000$
2Owen TippettXX100.00814593747565867139637064255758050650223650,000$
3Oliver WahlstromX100.00795972807762846938627160415859050640212925,001$
4Nicholas MerkleyX100.007543997968627669566760762547470506402411,100,000$
5Nicolas Aube-KubelX100.008454817668568860326368682561610506302511,573,000$
6Radim ZohornaXXX100.00794591688556646737696268254646050620253792,500$
7Ty Dellandrea (R)XX100.00747182757174776480596465614646050620213863,333$
8Kyle RauXXX100.00646172686163636880626862655152050610281600,000$
9Nolan Foote (R)X100.00757476767469726150576164584545050610202894,167$
10Brett MurrayX100.00737867698764766125666061254545050600233775,000$
11Jansen HarkinsXX100.00695293676854775857555965256162050590241750,000$
12Fredrik KarlstromX100.00807397667360615771496165584444050580233700,000$
13Jake WalmanX100.00734293746564646425514874255859050630251910,000$
14Kale ClagueX100.006341837665706769255648662550500506102341,700,000$
15Brendan GuhleX100.00757378797357614725354164395959050590243650,000$
16Jeremy DaviesX100.00696676686665685525514360414646050570241925,000$
17Simon Lundmark (R)X100.00807591707551524725384163394444050560204850,833$
Rayé
MOYENNE D’ÉQUIPE100.0075598473726272624357586537525205061
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 Nedeljkovic100.00697673706870697067697555560506702532,800,000$
2Spencer Martin100.0059496173626460656665304444050600262750,000$
3Ukko-Pekka Luukkonen (R)100.0050516488505150555151304545050540221778,333$
Rayé
MOYENNE D’ÉQUIPE100.005959667760626063616245484805060
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
1Nolan FooteSeattle (SEA)LW106814710013153282618.75%119719.75011127000001038.10%2100011.4200000110
2Nicholas MerkleySeattle (SEA)RW1038114208364014337.50%622822.800005270000291046.03%6300000.9600000022
3Oliver WahlstromSeattle (SEA)RW105383215272348152410.42%217317.33000010000230053.85%1300010.9200000201
4Kyle RauSeattle (SEA)C/LW/RW103582003243082110.00%016516.5700001000051056.35%19700000.9700000010
5William CarrierSeattle (SEA)LW9088-44036232910320.00%222825.410223240002380043.12%10900000.7000000000
6Ty DellandreaSeattle (SEA)C/RW1053834012244352011.63%120120.19000527000030058.37%25700000.7900000000
7Brett MurraySeattle (SEA)LW10257160109246128.33%117317.36000000002160031.25%1600000.8100000000
8Jeremy DaviesSeattle (SEA)D100666601764440.00%1622622.67000222000039000.00%000000.5300000000
9Nicolas Aube-KubelSeattle (SEA)RW101459401916193145.26%1317217.2700000000151025.00%800000.5800000010
10Kale ClagueSeattle (SEA)D10224-11202015175811.76%2626426.492021230000143000.00%000000.3000000000
11Owen TippettSeattle (SEA)LW/RW9224-420718369255.56%121123.550116240002400133.33%1800000.3800000001
12Radim ZohornaSeattle (SEA)C/LW/RW10224-500721329236.25%218618.690001025000020038.96%23100000.4300000000
13Jake WalmanSeattle (SEA)D10213-1220028151851311.11%2725225.27112729000030000.00%000000.2400000000
14Simon LundmarkSeattle (SEA)D100331120101154030.00%1217217.2500012000017000.00%000000.3500002000
15Jansen HarkinsSeattle (SEA)C/LW101120002553220.00%0444.4800000000010048.21%5600000.8900000000
16Fredrik KarlstromSeattle (SEA)C10101-2203662216.67%2454.5800000000050080.00%500000.4400000000
17Brendan GuhleSeattle (SEA)D9011317520311210.00%1820122.34000521000030000.00%000000.1000001000
Statistiques d’équipe totales ou en moyenne16735629711120202432643981082638.79%130314818.853585726600083344148.89%99400020.6200003354
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)61500.9063.8635820232450010.00%060100
Statistiques d’équipe totales ou en moyenne61500.9063.863582023245001060100


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 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 10Link
Alex NedeljkovicSeattle (SEA)G251996-01-07No189 Lbs6 ft0NoNoNo3Pro & Farm2,800,000$0$0$No2,800,000$2,800,000$Lien
Brendan GuhleSeattle (SEA)D241997-07-29No197 Lbs6 ft2NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Brett MurraySeattle (SEA)LW231998-07-19No228 Lbs6 ft5NoNoNo3Pro & Farm775,000$0$0$No775,000$775,000$Lien
Fredrik KarlstromSeattle (SEA)C231998-01-12No196 Lbs6 ft2NoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$Lien
Jake WalmanSeattle (SEA)D251996-02-20No170 Lbs6 ft1NoNoNo1Pro & Farm910,000$0$0$NoLien
Jansen HarkinsSeattle (SEA)C/LW241997-05-23No182 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$NoLien
Jeremy DaviesSeattle (SEA)D241996-12-04No180 Lbs5 ft11NoNoNo1Pro & Farm925,000$0$0$NoLien
Kale ClagueSeattle (SEA)D231998-06-05No177 Lbs6 ft0NoNoNo4Pro & Farm1,700,000$0$0$No1,700,000$1,700,000$1,700,000$Lien
Kyle Rau (contrat à 1 volet)Seattle (SEA)C/LW/RW281992-10-24No176 Lbs5 ft8YesNoNo1Pro & Farm600,000$0$0$NoLien
Nicholas MerkleySeattle (SEA)RW241997-05-23No194 Lbs5 ft10NoNoYes1Pro & Farm1,100,000$0$0$NoLien
Nicolas Aube-KubelSeattle (SEA)RW251996-05-09No187 Lbs5 ft11NoNoNo1Pro & Farm1,573,000$0$0$NoLien
Nolan FooteSeattle (SEA)LW202000-11-29Yes196 Lbs6 ft3NoNoNo2Pro & Farm894,167$0$0$No894,167$Lien
Oliver WahlstromSeattle (SEA)RW212000-06-13No205 Lbs6 ft2NoNoNo2Pro & Farm925,001$0$0$No925,001$Lien
Owen TippettSeattle (SEA)LW/RW221999-02-16No207 Lbs6 ft1NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Radim ZohornaSeattle (SEA)C/LW/RW251996-04-29No220 Lbs6 ft6NoNoNo3Pro & Farm792,500$0$0$No792,500$792,500$Lien
Simon LundmarkSeattle (SEA)D202000-10-08Yes201 Lbs6 ft2NoNoNo4Pro & Farm850,833$0$0$No850,833$850,833$850,833$Lien
Spencer Martin (contrat à 1 volet)Seattle (SEA)G261995-06-08No191 Lbs6 ft1NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Ty DellandreaSeattle (SEA)C/RW212000-07-20Yes190 Lbs6 ft1NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien
Ukko-Pekka LuukkonenSeattle (SEA)G221999-03-08Yes220 Lbs6 ft4NoNoNo1Pro & Farm778,333$0$0$NoLien
William Carrier (contrat à 1 volet)Seattle (SEA)LW261994-12-20No218 Lbs6 ft2NoNoNo2Pro & Farm1,100,000$200,000$0$No1,100,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2023.55196 Lbs6 ft12.201,004,358$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1William CarrierRadim ZohornaOwen Tippett40122
2Nolan FooteTy DellandreaNicholas Merkley30122
3Brett MurrayKyle RauOliver Wahlstrom20122
4William CarrierJansen HarkinsNicolas Aube-Kubel10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanKale Clague40122
2Brendan GuhleJeremy Davies30122
3Simon LundmarkNicolas Aube-Kubel20122
4Jake WalmanKale Clague10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1William CarrierRadim ZohornaOwen Tippett60122
2Nolan FooteTy DellandreaNicholas Merkley40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanKale Clague60122
2Brendan GuhleJeremy Davies40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1William CarrierOwen Tippett60122
2Nicholas MerkleyOliver Wahlstrom40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanKale Clague60122
2Brendan GuhleJeremy Davies40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1William Carrier60122Jake WalmanKale Clague60122
2Owen Tippett40122Brendan GuhleJeremy Davies40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1William CarrierOwen Tippett60122
2Nicholas MerkleyOliver Wahlstrom40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanKale Clague60122
2Brendan GuhleJeremy Davies40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
William CarrierRadim ZohornaOwen TippettJake WalmanKale Clague
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
William CarrierRadim ZohornaOwen TippettJake WalmanKale Clague
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Fredrik Karlstrom, Kyle Rau, Brett MurrayFredrik Karlstrom, Kyle RauBrett Murray
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Simon Lundmark, Brendan Guhle, Jeremy DaviesSimon LundmarkBrendan Guhle, Jeremy Davies
Tirs de pénalité
William Carrier, Owen Tippett, Nicholas Merkley, Oliver Wahlstrom, Nicolas Aube-Kubel
Gardien
#1 : Alex Nedeljkovic, #2 : Spencer Martin


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
1Caroline64200000262243210000013121321000001310380.667264571001611622491479711440258787614717317.65%33584.85%018940846.32%20040249.75%9718452.72%2471662628114170
2Comets40400000918-92020000069-32020000039-600.000917261016116214914797114401625246961200.00%17570.59%018940846.32%20040249.75%9718452.72%2471662628114170
Total1046000003540-5523000001921-2523000001619-380.40035629710161162398147971144042013012224329310.34%501080.00%018940846.32%20040249.75%9718452.72%2471662628114170
_Since Last GM Reset1046000003540-5523000001921-2523000001619-380.40035629710161162398147971144042013012224329310.34%501080.00%018940846.32%20040249.75%9718452.72%2471662628114170
_Vs Conference1046000003540-5523000001921-2523000001619-380.40035629710161162398147971144042013012224329310.34%501080.00%018940846.32%20040249.75%9718452.72%2471662628114170
_Vs Division40000000918-92000000069-32000000039-600.000917261016116214914797114401625246961200.00%17570.59%018940846.32%20040249.75%9718452.72%2471662628114170

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
108L435629739842013012224310
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
104600003540
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
52300001921
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
52300001619
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
29310.34%501080.00%0
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
1479711440161162
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
18940846.32%20040249.75%9718452.72%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2471662628114170


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
2 - 2023-04-185Caroline5Seattle4BLSommaire du match
4 - 2023-04-2013Caroline5Seattle6BWXSommaire du match
6 - 2023-04-2221Seattle6Caroline5AWXSommaire du match
8 - 2023-04-2429Seattle3Caroline4ALSommaire du match
10 - 2023-04-2637Caroline2Seattle3BWSommaire du match
12 - 2023-04-2845Seattle4Caroline1AWSommaire du match
16 - 2023-05-0259Comets6Seattle4BLSommaire du match
18 - 2023-05-0463Comets3Seattle2BLSommaire du match
20 - 2023-05-0667Seattle0Comets4ALSommaire du match
22 - 2023-05-0871Seattle3Comets5ALSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité40002000
Prix des billets3515
Assistance20,00010,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
36 6000 - 100.00% 170,000$850,000$6000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 1,763,716$ 1,763,716$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

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




Seattle Leaders statistiques (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 (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