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Red Wings
GP: 82 | W: 40 | L: 33 | OTL: 9 | P: 89
GF: 272 | GA: 284 | PP%: 16.52% | PK%: 80.43%
DG: Martin Dufour | Morale : 31 | Moyenne d’équipe : 68

Centre de jeu
Canadiens
50-26-6, 106pts
5
1 Red Wings
40-33-9, 89pts
Team Stats
L1SéquenceL2
25-14-2Fiche domicile21-16-4
25-12-4Fiche domicile19-17-5
6-3-1Derniers 10 matchs4-5-1
3.59Buts par match 3.32
3.23Buts contre par match 3.46
19.10%Pourcentage en avantage numérique16.52%
81.82%Pourcentage en désavantage numérique80.43%
Red Wings
40-33-9, 89pts
2
3 Devils
33-36-13, 79pts
Team Stats
L2SéquenceW1
21-16-4Fiche domicile19-16-6
19-17-5Fiche domicile14-20-7
4-5-1Derniers 10 matchs4-4-2
3.32Buts par match 2.99
3.46Buts contre par match 3.51
16.52%Pourcentage en avantage numérique12.23%
80.43%Pourcentage en désavantage numérique79.42%
Meneurs d'équipe
Buts
Logan O'Connor
35
Passes
Pius Suter
46
Points
Logan O'Connor
76
Plus/Moins
Teddy Blueger
15
Victoires
Joel Hofer
30
Pourcentage d’arrêts
Justus Annunen
0.895

Statistiques d’équipe
Buts pour
272
3.32 GFG
Tirs pour
2592
31.61 Avg
Pourcentage en avantage numérique
16.5%
38 GF
Début de zone offensive
38.4%
Buts contre
284
3.46 GAA
Tirs contre
2626
32.02 Avg
Pourcentage en désavantage numérique
80.4%%
45 GA
Début de la zone défensive
36.7%
Informations de l'équipe

Directeur généralMartin Dufour
EntraîneurKirk Muller
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,585
Billets de saison2,400


Informations de la formation

Équipe Pro36
Équipe Mineure18
Limite Contrat54 / 68
Espoirs54


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
1Logan O'Connor (R)X100.0084638487729086845292818225887956527902911,500,000$
2Dominik Kubalik (R)X100.0076488576757583964790986325907545597803013,000,000$
3Oskar Lindblom (R)X100.0067359975747286834993927525878357537702912,000,000$
4Pius Suter (R)X100.0069419384708680887484847725886848287602912,500,000$
5Teddy Blueger (R)X100.0086616878717883778078708625838155487403121,500,000$
6A.J. Greer (R)X100.008881577484798974507167712573847266700291800,000$
7Wade Allison (R)X100.008559737577807875376769682582694464690282800,000$
8Cole Koepke (R)X100.008345927582828074406771712575614957692271842,500$
9Logan Brown (R)X100.005228947080747665556963672576835654660282600,000$
10Elmer Soderblom (R)X100.006840826999847069506664642569614943662241878,333$
11John Hayden (R)X100.007355607087777466556161662567847257650313575,000$
12Jeffrey Truchon-Viel (R)X100.006464506565706864446357672562585017600292575,000$
13Juuso Valimaki (R)X100.0063448674788585974091838025858056257702733,000,000$
14Cam York (R)X100.0073408189769079854081768125846849457602522,000,000$
15Urho Vaakanainen (R)X100.0062408475848582724074688225757967597302731,500,000$
16Jamie Drysdale (R)X100.006540888679898576407272742579715921720242700,000$
17Justin BraunX100.006231986076739056255251887099991537003921,500,000$
18Madison Bowey (R)X100.0084809166757678703071666951908435636903131,000,000$
Rayé
1Dylan Guenther (R)X100.007140848982878088508084712588614952762232894,167$
2Noah Ostlund (R)X100.006241737356626063446160672565505020600223886,667$
3Par Lindholm (R)X100.003613996870728345864443806198871419590343575,000$
4Danil Gushchin (R)X100.005443686661656367456364512566515020582231828,333$
5Milos Kelemen (R)X100.006445626374646363436059582565564820582261817,500$
6Connor Bunnaman (R)X100.005929996476496642686055672573725619570281575,000$
7Gabriel Fortier (R)X100.005232787168576355575348622568564520560263575,000$
8Fredrik Karlstrom (R)X100.005432806575596454525247602565574620551281750,000$
9Scott Reedy (R)X100.008076896177535356703838655750505520530273575,000$
10Kaedan Korczak (R)X100.006640827384847369407060712567655519680253800,000$
11Joe MorrowX100.0050209966746972713065727554918051206703311,000,000$
12Isaiah George (R)X100.005640827583846569406463682569525020650223838,833$
13Dylan Coghlan (R)X100.004025907176766556406260762571654820640282600,000$
14Sami Niku (R)X100.006232857471624855246358692579764120630292575,000$
15Lassi Thomson (R)X100.005940707173626265406356672568544620620253575,000$
MOYENNE D’ÉQUIPE100.00664482737674746948686571307770493667
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
1Joel Hofer (R)100.008484847787908690888550776657708202531,500,000$
2Justus Annunen (R)99.008185868888888086868550786558718202631,500,000$
Rayé
1Josef Korenar (R)100.00757671757496979190737277814920800282900,000$
MOYENNE D’ÉQUIPE99.6780828080839188898881577771555481
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kirk Muller7275706771661CAN591800,000$


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
1Logan O'ConnorRed Wings (DET)RW82354176-1463151871542466613614.23%51171220.89116173521400001965442.26%4527039110.89010111672
2Dominik KubalikRed Wings (DET)LW78343670-86410155992517014413.55%30163320.94512172720500051868140.54%1484629100.8609011455
3Oskar LindblomRed Wings (DET)RW8129386710201221182537614611.46%33153418.955611211712026914146.77%1244428000.8707000615
4Dylan GuentherRed Wings (DET)LW7029336292801141002627916411.07%26131618.81448211560114711234.78%698419010.9413000333
5Pius SuterRed Wings (DET)C69144660-1660100141157551258.92%24127718.5241418241730111152052.68%15303421000.9414000213
6Teddy BluegerRed Wings (DET)C792235571512440184168111417419.82%39136117.2336912171000034154.02%14941927000.8400224241
7Wade AllisonRed Wings (DET)RW8225224702915154791825011913.74%25101712.41000011000003438.64%443320000.9200201338
8A.J. GreerRed Wings (DET)LW82182341-41937519570155368811.61%30116314.190002340000562038.61%1011917000.7000852311
9Cam YorkRed Wings (DET)D8053439-133513917018666682.69%103189423.68212142323400010206010%02657000.4101001010
10Juuso ValimakiRed Wings (DET)D6782533136107213715046575.33%85158623.684711201990006182120%03550000.4201002012
11Cole KoepkeRed Wings (DET)LW821417313407862151561079.27%1282710.09000020000814133.33%632916000.7500000051
12Logan BrownRed Wings (DET)C82121729-6004111867272817.91%23109513.370000360002360239.76%840826000.5301000021
13Urho VaakanainenRed Wings (DET)D823222534010751208135313.70%99173621.1700011490000134000%01265100.2900101100
14Jamie DrysdaleRed Wings (DET)D7732023-335257913010351432.91%76165921.5502251520000147100%03046000.2801131000
15John HaydenRed Wings (DET)C82515203435825050182210.00%146788.2700003000000044.60%27827000.5900100110
16Madison BoweyRed Wings (DET)D8201616-29440100864322270%75126415.4200004000025000%01152000.2522314010
17Justin BraunRed Wings (DET)D8221214-900541275314303.77%73140017.07000246000049100%0741000.2023000003
18Elmer SoderblomRed Wings (DET)RW827613080384757205012.28%86247.62000020000151036.84%19710000.4200000000
19Noah OstlundRed Wings (DET)C1534716012763450.00%01077.1400000000000154.55%4413001.3100000200
20Kaedan KorczakRed Wings (DET)D21066620101336156110%2332915.6700000000011000%0211000.3600002001
21Jeffrey Truchon-VielRed Wings (DET)LW15112-160177105410.00%21107.3700000000020050.00%201000.3600000000
22Par LindholmRed Wings (DET)LW1011-100000000%066.400000000000000%000003.1300000000
23Connor BunnamanRed Wings (DET)C1000000000000%066.700000000000000%10000000000000
Statistiques d’équipe totales ou en moyenne1474269470739-14834260201120262589842147810.39%8512434416.5238691071931968224341516372048.24%5209519585320.61642191320333636
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
1Joel HoferRed Wings (DET)60302350.8943.303401201871768757410.714285626143
2Justus AnnunenRed Wings (DET)30101040.8953.4515650090857404000.727112656122
Statistiques d’équipe totales ou en moyenne90403390.8943.354967202772625116141398282265


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
A.J. GreerRed Wings (DET)LW291996-12-14CANYes209 Lbs6 ft3NoNoTrade2025-09-01NoNo1FalseFalsePro & Farm800,000$4,082$0$0$No---------------------------
Cam YorkRed Wings (DET)D252001-01-05USAYes194 Lbs6 ft0NoNoN/ANoNo22024-09-08FalseFalsePro & Farm2,000,000$10,204$0$0$No2,000,000$-----------------No--------
Cole KoepkeRed Wings (DET)LW271998-05-17USAYes207 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm842,500$4,298$0$0$No---------------------------
Connor BunnamanRed Wings (DET)C281998-04-16CANYes207 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm575,000$2,934$0$0$No---------------------------
Danil GushchinRed Wings (DET)RW232002-06-02RUSYes181 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm828,333$4,226$0$0$No---------------------------
Dominik KubalikRed Wings (DET)LW301995-08-21CZEYes192 Lbs6 ft2NoNoN/ANoNo12025-08-10FalseFalsePro & Farm3,000,000$15,306$0$0$No---------------------------
Dylan CoghlanRed Wings (DET)D281998-02-19CANYes205 Lbs6 ft2NoNoN/ANoNo22024-09-08FalseFalsePro & Farm600,000$3,061$0$0$No600,000$-----------------No--------
Dylan GuentherRed Wings (DET)LW232003-04-10CANYes191 Lbs6 ft1NoNoAssign ManuallyNoNo22024-08-17FalseFalsePro & Farm894,167$4,562$0$0$No894,167$--------894,167$--------No--------
Elmer SoderblomRed Wings (DET)RW242001-07-05SWEYes246 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm878,333$4,481$0$0$No---------------------------
Fredrik KarlstromRed Wings (DET)C281998-01-12SWEYes194 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm750,000$3,827$0$0$No---------------------------
Gabriel FortierRed Wings (DET)LW262000-02-06CANYes172 Lbs5 ft10NoNoN/ANoNo32025-08-10FalseFalsePro & Farm575,000$2,934$0$0$No575,000$575,000$-------575,000$575,000$-------NoNo-------
Isaiah GeorgeRed Wings (DET)D222004-02-15CANYes196 Lbs6 ft1NoNoAssign ManuallyNoNo32025-09-06FalseFalsePro & Farm838,833$4,280$0$0$No838,833$838,833$-------838,833$838,833$-------NoNo-------
Jamie DrysdaleRed Wings (DET)D242002-04-08CANYes185 Lbs5 ft11NoNoN/ANoNo22024-09-08FalseFalsePro & Farm700,000$3,571$0$0$No700,000$-----------------No--------
Jeffrey Truchon-VielRed Wings (DET)LW291997-01-28CANYes205 Lbs6 ft2NoNoTrade2024-12-22NoNo22024-09-18FalseFalsePro & Farm575,000$2,934$0$0$No575,000$--------575,000$--------No--------
Joe MorrowRed Wings (DET)D331992-12-09CANNo196 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,000,000$5,102$0$0$No---------------------------
Joel HoferRed Wings (DET)G252000-07-30CANYes179 Lbs6 ft5NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,500,000$7,653$0$0$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
John HaydenRed Wings (DET)C311995-02-14USAYes223 Lbs6 ft3NoNoN/ANoNo32025-08-10FalseFalsePro & Farm575,000$2,934$0$0$No575,000$575,000$-------575,000$575,000$-------NoNo-------
Josef KorenarRed Wings (DET)G281998-01-31CZEYes185 Lbs6 ft1NoNoN/ANoNo22024-09-08FalseFalsePro & Farm900,000$4,592$0$0$No900,000$-----------------No--------
Justin BraunRed Wings (DET)D391987-02-10USANo208 Lbs6 ft2NoNoFree AgentNoNo22024-10-06FalseFalsePro & Farm1,500,000$7,653$0$0$No1,500,000$--------1,500,000$--------No--------
Justus AnnunenRed Wings (DET)G262000-03-11FINYes210 Lbs6 ft4NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,500,000$7,653$0$0$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Juuso ValimakiRed Wings (DET)D271998-10-06FINYes205 Lbs6 ft2NoNoN/ANoNo32025-08-10FalseFalsePro & Farm3,000,000$15,306$0$0$No3,000,000$3,000,000$-------3,000,000$3,000,000$-------NoNo-------
Kaedan KorczakRed Wings (DET)D252001-01-29CANYes203 Lbs6 ft3NoNoN/ANoNo32025-08-10FalseFalsePro & Farm800,000$4,082$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------
Lassi ThomsonRed Wings (DET)D252000-09-24FINYes190 Lbs6 ft0NoNoN/ANoNo32025-08-10FalseFalsePro & Farm575,000$2,934$0$0$No575,000$575,000$-------575,000$575,000$-------NoNo-------
Logan BrownRed Wings (DET)C281998-03-05USAYes218 Lbs6 ft6NoNoN/ANoNo22024-09-08FalseFalsePro & Farm600,000$3,061$0$0$No600,000$-----------------No--------
Logan O'ConnorRed Wings (DET)RW291996-08-14CANYes175 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,500,000$7,653$0$0$No---------------------------
Madison BoweyRed Wings (DET)D311995-04-22CANYes198 Lbs6 ft2NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,000,000$5,102$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------
Milos KelemenRed Wings (DET)RW261999-07-06SLVYes218 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm817,500$4,171$0$0$No---------------------------
Noah OstlundRed Wings (DET)C222004-03-11SWEYes165 Lbs5 ft11NoNoAssign ManuallyNoNo32025-09-06FalseFalsePro & Farm886,667$4,524$0$0$No886,667$886,667$-------886,667$886,667$-------NoNo-------
Oskar LindblomRed Wings (DET)RW291996-08-15SWEYes191 Lbs6 ft1NoNoN/ANoNo12024-09-08FalseFalsePro & Farm2,000,000$10,204$0$0$No---------------------------
Par LindholmRed Wings (DET)LW341991-10-05SWEYes183 Lbs5 ft11NoNoFree AgentNoNo32025-09-21FalseFalsePro & Farm575,000$2,934$0$0$No575,000$575,000$-------575,000$575,000$-------NoNo-------
Pius SuterRed Wings (DET)C291996-05-24SUIYes179 Lbs5 ft11NoNoN/ANoNo12024-09-08FalseFalsePro & Farm2,500,000$12,755$0$0$No---------------------------
Sami NikuRed Wings (DET)D291996-10-10FINYes176 Lbs6 ft1NoNoN/ANoNo22025-08-10FalseFalsePro & Farm575,000$2,934$0$0$No575,000$--------575,000$--------No--------
Scott ReedyRed Wings (DET)C271999-04-04USAYes214 Lbs6 ft2NoNoN/ANoNo32025-08-10FalseFalsePro & Farm575,000$2,934$0$0$No575,000$575,000$-------575,000$575,000$-------NoNo-------
Teddy BluegerRed Wings (DET)C311994-08-15LVAYes185 Lbs6 ft0NoNoN/ANoNo22024-09-08FalseFalsePro & Farm1,500,000$7,653$0$0$No1,500,000$-----------------No--------
Urho VaakanainenRed Wings (DET)D271999-01-01FINYes205 Lbs6 ft2NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,500,000$7,653$0$0$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Wade AllisonRed Wings (DET)RW281997-10-14CANYes205 Lbs6 ft2NoNoN/ANoNo22024-09-08FalseFalsePro & Farm800,000$4,082$0$0$No800,000$-----------------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3627.64197 Lbs6 ft22.031,112,120$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dominik KubalikPius SuterLogan O'Connor35122
2A.J. GreerTeddy BluegerOskar Lindblom35122
3Cole KoepkeLogan BrownWade Allison25122
4Jeffrey Truchon-VielJohn HaydenElmer Soderblom5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCam York35122
2Urho VaakanainenJamie Drysdale35122
3Madison BoweyJustin Braun30122
4Juuso ValimakiCam York0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dominik KubalikPius SuterLogan O'Connor60122
2A.J. GreerTeddy BluegerOskar Lindblom40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCam York60122
2Urho VaakanainenJamie Drysdale40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Logan O'ConnorDominik Kubalik60122
2Oskar LindblomPius Suter40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCam York60122
2Urho VaakanainenJamie Drysdale40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Logan O'Connor60122Juuso ValimakiCam York60122
2Dominik Kubalik40122Urho VaakanainenJamie Drysdale40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Logan O'ConnorDominik Kubalik60122
2Oskar LindblomPius Suter40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCam York60122
2Urho VaakanainenJamie Drysdale40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dominik KubalikPius SuterLogan O'ConnorJuuso ValimakiCam York
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dominik KubalikPius SuterLogan O'ConnorJuuso ValimakiCam York
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Wade Allison, Cole Koepke, Elmer SoderblomWade Allison, Cole KoepkeElmer Soderblom
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Madison Bowey, Justin Braun, Urho VaakanainenMadison BoweyJustin Braun, Urho Vaakanainen
Tirs de pénalité
Logan O'Connor, Dominik Kubalik, Oskar Lindblom, Pius Suter, Teddy Blueger
Gardien
#1 : Justus Annunen, #2 : Joel Hofer
Lignes d’attaque personnalisées en prolongation
Logan O'Connor, Dominik Kubalik, Oskar Lindblom, Pius Suter, Teddy Blueger, A.J. Greer, Wade Allison, Cole Koepke, Elmer Soderblom, Logan Brown
Lignes de défense personnalisées en prolongation
Juuso Valimaki, Cam York, Urho Vaakanainen, Jamie Drysdale, Madison Bowey


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
TotalDomicile Visiteur
# 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 RI
1Avalanche31200000990211000008621010000013-220.333916250078101879105875917776648937665500.00%3166.67%1997198450.25%899189447.47%617128248.13%1775105917977271402699
2Blackhawks21001000853100010004311100000042241.00081422007810187960875917776647120450300.00%20100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
3Blues330000001257220000008351100000042261.000122133007810187910487591777664973210656116.67%50100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
4Bruins624000001829-1131200000912-331200000917-840.333183149007810187919187591777664201578715724312.50%22672.73%0997198450.25%899189447.47%617128248.13%1775105917977271402699R5
5Canadiens603002012236-14302000011019-9301002001217-530.250224062007810187919387591777664200559417424520.83%321068.75%0997198450.25%899189447.47%617128248.13%1775105917977271402699R5
6Canucks22000000963110000006421100000032141.000917260078101879738759177766465156534125.00%3166.67%0997198450.25%899189447.47%617128248.13%1775105917977271402699
7Capitals42100001141042200000010372010000147-350.6251426400078101879135875917776641203130818112.50%10280.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699R2
8Devils4110110013130210001005502010100088050.6251321340078101879116875917776641376136851317.69%8187.50%0997198450.25%899189447.47%617128248.13%1775105917977271402699
9Ducks22000000743110000003211100000042241.0007121900781018796287591777664601212534125.00%6266.67%0997198450.25%899189447.47%617128248.13%1775105917977271402699
10Flames32100000770110000003212110000045-140.66771118007810187911387591777664883876311436.36%10100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
11Flyers422000001314-1211000007702110000067-140.50013233600781018791458759177766414653148812216.67%7357.14%0997198450.25%899189447.47%617128248.13%1775105917977271402699R2
12Islanders421000101415-12110000059-42100001096360.75014223600781018791238759177766413144611009222.22%13469.23%1997198450.25%899189447.47%617128248.13%1775105917977271402699R2
13Kings320010001376110000005142100100086261.0001323360078101879988759177766482375775120.00%000%0997198450.25%899189447.47%617128248.13%1775105917977271402699
14Maple Leafs632000012523231200000912-3320000011611570.5832542670078101879186875917776642056710016825520.00%20575.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699R5
15Oilers20100010440100000102111010000023-120.500459007810187972875917776645416647000%30100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
16Penguins413000001016-62110000078-12020000038-520.25010162600781018791088759177766413940189110110.00%90100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699R2
17Predators2020000035-21010000023-11010000012-100.000358007810187958875917776647216154011100.00%50100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
18Rangers42100001161242110000010642100000166050.6251629451078101879125875917776641254018945120.00%9188.89%0997198450.25%899189447.47%617128248.13%1775105917977271402699R2
19Sabres622000022324-1301000021216-432100000118360.5002341640078101879161875917776641685814717027518.52%36780.56%0997198450.25%899189447.47%617128248.13%1775105917977271402699R5
20Senateurs632000102117431100010109132100000118380.667213657007810187917687591777664187551331542926.90%25196.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
21Sharks2020000027-51010000023-11010000004-400.000235007810187960875917776646125252200.00%10100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
22Stars2110000046-2110000003211010000014-320.50047110078101879568759177766469261243000%60100.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
23Wild20200000510-51010000035-21010000025-300.000591400781018797287591777664591813433133.33%4175.00%0997198450.25%899189447.47%617128248.13%1775105917977271402699
Total82343303336272284-1241181601123143141241161702213129143-14890.5432724707421078101879259287591777664262685383620132303816.52%2304580.43%2997198450.25%899189447.47%617128248.13%1775105917977271402699
_Since Last GM Reset82343303336272284-1241181601123143141241161702213129143-14890.5432724707421078101879259287591777664262685383620132303816.52%2304580.43%2997198450.25%899189447.47%617128248.13%1775105917977271402699
_Vs Conference54202201326189209-202710120011394106-122710100121395103-8550.5091893275161078101879165987591777664175956173813621862815.05%1914079.06%1997198450.25%899189447.47%617128248.13%1775105917977271402699
_Vs Division30101300214109129-201538000135068-181575002015961-2280.4671091902990078101879907875917776649612925618231292015.50%1352978.52%0997198450.25%899189447.47%617128248.13%1775105917977271402699

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8289L227247074225922626853836201310
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8234333336272284
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4118161123143141
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4116172213129143
Derniers 10 matchs
WLOTWOTL SOWSOL
450001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2303816.52%2304580.43%2
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
8759177766478101879
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
997198450.25%899189447.47%617128248.13%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1775105917977271402699


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
13Sabres6Red Wings4LR5Sommaire du match
310Red Wings2Canadiens3LXR5Sommaire du match
521Red Wings3Sabres2WSommaire du match
836Red Wings4Bruins6LR5Sommaire du match
945Senateurs1Red Wings4WR5Sommaire du match
1362Canadiens8Red Wings4LR5Sommaire du match
1778Red Wings6Maple Leafs7LXXSommaire du match
1988Red Wings5Senateurs2WR5Sommaire du match
2096Maple Leafs3Red Wings4WR5Sommaire du match
23110Bruins5Red Wings1LSommaire du match
27129Senateurs4Red Wings1LR5Sommaire du match
31151Avalanche3Red Wings6WSommaire du match
33163Red Wings3Flames1WSommaire du match
35171Flyers3Red Wings2LR2Sommaire du match
38187Red Wings1Capitals3LR2Sommaire du match
40196Islanders3Red Wings4WSommaire du match
42208Red Wings3Canucks2WSommaire du match
44219Red Wings6Maple Leafs2WR5Sommaire du match
46226Avalanche3Red Wings2LSommaire du match
48243Islanders6Red Wings1LR2Sommaire du match
54264Red Wings1Stars4LSommaire du match
55272Wild5Red Wings3LSommaire du match
59290Oilers1Red Wings2WXXSommaire du match
63314Flyers4Red Wings5WR2Sommaire du match
65329Red Wings1Senateurs3LR5Sommaire du match
66336Senateurs4Red Wings5WXXSommaire du match
68346Red Wings2Penguins6LR2Sommaire du match
71362Blackhawks3Red Wings4WXSommaire du match
74372Red Wings4Ducks2WSommaire du match
76382Red Wings4Kings3WSommaire du match
77388Maple Leafs4Red Wings2LR5Sommaire du match
80402Red Wings3Capitals4LXXR2Sommaire du match
81412Flames2Red Wings3WSommaire du match
85431Red Wings2Wild5LSommaire du match
86437Canucks4Red Wings6WSommaire du match
91458Red Wings0Sharks4LSommaire du match
92460Maple Leafs5Red Wings3LR5Sommaire du match
95475Red Wings4Bruins2WSommaire du match
96484Ducks2Red Wings3WSommaire du match
99494Red Wings2Oilers3LSommaire du match
102508Rangers1Red Wings7WR2Sommaire du match
104521Red Wings4Sabres5LR5Sommaire du match
105531Rangers5Red Wings3LSommaire du match
107544Red Wings4Maple Leafs2WR5Sommaire du match
109556Stars2Red Wings3WSommaire du match
111565Red Wings1Bruins9LR5Sommaire du match
113578Red Wings5Canadiens6LXR5Sommaire du match
114584Capitals2Red Wings7WSommaire du match
118604Capitals1Red Wings3WR2Sommaire du match
120610Red Wings2Rangers1WSommaire du match
123626Red Wings4Sabres1WR5Sommaire du match
124631Devils2Red Wings3WSommaire du match
127646Red Wings5Senateurs3WR5Sommaire du match
128656Bruins3Red Wings5WSommaire du match
131672Red Wings6Devils5WXR2Sommaire du match
132678Bruins4Red Wings3LR5Sommaire du match
136697Red Wings5Canadiens8LR5Sommaire du match
138703Sabres6Red Wings5LXXSommaire du match
140712Red Wings5Islanders3WR2Sommaire du match
142725Kings1Red Wings5WSommaire du match
145743Red Wings4Kings3WXSommaire du match
147752Red Wings5Flyers4WR2Sommaire du match
148755Devils3Red Wings2LXSommaire du match
151770Red Wings1Avalanche3LSommaire du match
152778Penguins4Red Wings5WR2Sommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
155796Red Wings1Penguins2LSommaire du match
156800Red Wings1Flames4LSommaire du match
158808Penguins4Red Wings2LR2Sommaire du match
160824Red Wings4Rangers5LXXSommaire du match
161830Sabres4Red Wings3LXXR5Sommaire du match
164845Red Wings1Flyers3LSommaire du match
165849Red Wings4Blues2WSommaire du match
167858Predators3Red Wings2LSommaire du match
171876Red Wings4Islanders3WXXR2Sommaire du match
172883Blues2Red Wings5WSommaire du match
174899Red Wings4Blackhawks2WSommaire du match
176904Blues1Red Wings3WSommaire du match
180924Sharks3Red Wings2LSommaire du match
182934Red Wings1Predators2LSommaire du match
186952Canadiens6Red Wings5LXXR5Sommaire du match
191968Canadiens5Red Wings1LSommaire du match
193981Red Wings2Devils3LR2Sommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance65,73440,232
Assistance PCT80.16%98.13%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
0 2585 - 86.15% 130,516$5,351,173$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
4,808,418$ 4,003,633$ 4,003,633$ 800,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 4,012,489$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 24,508$ 24,508$




Red Wings 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

Red Wings 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

Red Wings 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

Red Wings 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

Red Wings 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