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Red Wings
GP: 6 | W: 2 | L: 4
GF: 18 | GA: 25 | PP%: 18.52% | PK%: 77.27%
DG: Martin Dufour | Morale : 1 | Moyenne d’équipe : 68

Centre de jeu
Red Wings
2-4-0, 4pts
3
6 Canadiens
6-6-0, 12pts
Team Stats
L2SéquenceL1
2-1-0Fiche domicile4-2-0
0-3-0Fiche domicile2-4-0
2-4-0Derniers 10 matchs4-4-2
3.00Buts par match 3.67
4.17Buts contre par match 3.25
18.52%Pourcentage en avantage numérique24.00%
77.27%Pourcentage en désavantage numérique84.78%
Canadiens
6-6-0, 12pts
6
2 Red Wings
2-4-0, 4pts
Team Stats
L1SéquenceL2
4-2-0Fiche domicile2-1-0
2-4-0Fiche domicile0-3-0
4-4-2Derniers 10 matchs2-4-0
3.67Buts par match 3.00
3.25Buts contre par match 4.17
24.00%Pourcentage en avantage numérique18.52%
84.78%Pourcentage en désavantage numérique77.27%
Meneurs d'équipe
Buts
Logan O'Connor
3
Passes
Dominik Kubalik
4
Points
Dominik Kubalik
6
Plus/Moins
Urho Vaakanainen
4
Victoires
Joel Hofer
2
Pourcentage d’arrêts
Joel Hofer
0.879

Statistiques d’équipe
Buts pour
18
3.00 GFG
Tirs pour
181
30.17 Avg
Pourcentage en avantage numérique
18.5%
5 GF
Début de zone offensive
37.5%
Buts contre
25
4.17 GAA
Tirs contre
187
31.17 Avg
Pourcentage en désavantage numérique
77.3%%
5 GA
Début de la zone défensive
37.8%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,665
Billets de saison2,400


Informations de la formation

Équipe Pro36
Équipe Mineure18
Limite Contrat54 / 68
Espoirs54


Historique d'équipe

Saison actuelle2-4
Historique82-68-16 (0.494%)
Apparitions en séries éliminatoires 0
Historique en séries éliminatoires (W-L)2 - 4 (0.333%)
Coupe Stanley0


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)X100.0084638487729086845292828225888056487902911,500,000$
2Dominik Kubalik (R)X100.0076488576757583964790986325907544587803013,000,000$
3Oskar Lindblom (R)X100.0067359975747286834993927525878356487702912,000,000$
4Pius Suter (R)X100.0069419384708680887484847725886848237603012,500,000$
5Dylan Guenther (R)X100.007140848982878088508084712588614946762232894,167$
6Teddy Blueger (R)X100.0086616878717883778078708625838155457403121,500,000$
7A.J. Greer (R)X100.008881567484798974507167712573847257700291800,000$
8Wade Allison (R)X100.008559737577807875376770682582694354690282800,000$
9Cole Koepke (R)X100.008345927582828074406770712575614951692281842,500$
10Logan Brown (R)X100.005228947080747665556963672576835648650282600,000$
11John Hayden (R)X100.007355597087777466556161662567847250650313575,000$
12Elmer Soderblom (R)X100.006840826999847069506664642569614938652241878,333$
13Juuso Valimaki (R)X100.0063448674788585974091838025858156207602733,000,000$
14Cam York (R)X100.0073408189769079854081768125846849397602522,000,000$
15Urho Vaakanainen (R)X100.0062408475848582724074688225757967547302731,500,000$
16Jamie Drysdale (R)X100.006540888679898576407272742579715918720242700,000$
17Madison Bowey (R)X100.0084809166757678703071666951908435546903131,000,000$
18Justin BraunX100.006231985976739056255251887099991466903921,500,000$
Rayé
1Jeffrey Truchon-Viel (R)X100.006464506565706864446357672562585020600292575,000$
2Noah Ostlund (R)X100.006241737356626063446160672565505020600223886,667$
3Par Lindholm (R)X100.003613996870728345864443806198871419590343575,000$
4Danil Gushchin (R)X100.005443686661656367456364512566515020582241828,333$
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’ÉQUIPE100.00664482737674746948686571307770493367
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)100.008484847787918689888550776657668202531,500,000$
2Justus Annunen (R)100.008185868888888086868550786557668202631,500,000$
Rayé
1Josef Korenar (R)100.00757671757496979190737277814922800282900,000$
MOYENNE D’ÉQUIPE100.0080828080839288898881577771545181
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
1Dominik KubalikRed Wings (DET)LW6246-21210941721011.76%412621.061233200000200033.33%952000.9500101001
2Logan O'ConnorRed Wings (DET)RW6336-41151910237613.04%312721.320223220000171051.28%3923000.9400001100
3Pius SuterRed Wings (DET)C6246-400717126216.67%411218.78213422000051059.18%14720001.0600000000
4Oskar LindblomRed Wings (DET)RW6235100515218129.52%311519.32101318000090037.50%1670000.8600000000
5Teddy BluegerRed Wings (DET)C614501351111142117.14%210317.20011118000000059.60%9942000.9700100001
6A.J. GreerRed Wings (DET)LW6224-2115163142414.29%310016.75000211000040055.56%902000.8000010000
7Urho VaakanainenRed Wings (DET)D6033420887340%812821.45000014000013000%016000.4700000001
8Wade AllisonRed Wings (DET)RW6303-51151172041015.00%17412.470000100000000%301000.8000010000
9Juuso ValimakiRed Wings (DET)D6112-10081275414.29%714824.82101125000122000%041000.2700000000
10John HaydenRed Wings (DET)C6022-32610672040%0447.4400000000000034.78%2320000.9000110000
11Cam YorkRed Wings (DET)D6022-12011147120%714724.64011025000021000%027000.2700000000
12Jamie DrysdaleRed Wings (DET)D6022400776520%912621.13000114000014000%013000.3200000000
13Jeffrey Truchon-VielRed Wings (DET)LW41011201630133.33%0256.460000000000010%000000.7700000000
14Elmer SoderblomRed Wings (DET)RW6011120346130%2457.5700000000050040.00%502000.4400000000
15Dylan GuentherRed Wings (DET)LW2101-1209494411.11%03919.500000500003000%110000.5100000000
16Madison BoweyRed Wings (DET)D6000-101010313400%68514.180002000000000%01400000011000
17Logan BrownRed Wings (DET)C6000-200262130%46410.7900000000030041.18%341200000000000
18Justin BraunRed Wings (DET)D6000-10004122010%68814.690000000000000%00400000000000
19Cole KoepkeRed Wings (DET)LW6000-100866050%26811.3900001000020075.00%40300000000000
Statistiques d’équipe totales ou en moyenne108183149-351045014815418155889.94%71177416.4357122020600011462153.21%3893342000.5500343103
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)42200.8793.6919500129940000033010
2Justus AnnunenRed Wings (DET)40200.8524.7016600138833000033000
Statistiques d’équipe totales ou en moyenne82400.8664.1436200251877300066010


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$0$0$No---------------------------
Cam YorkRed Wings (DET)D252001-01-05USAYes194 Lbs6 ft0NoNoN/ANoNo22024-09-08FalseFalsePro & Farm2,000,000$0$0$No2,000,000$-----------------No--------
Cole KoepkeRed Wings (DET)LW281998-05-17USAYes207 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm842,500$0$0$No---------------------------
Connor BunnamanRed Wings (DET)C281998-04-16CANYes207 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm575,000$0$0$No---------------------------
Danil GushchinRed Wings (DET)RW242002-06-02RUSYes181 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm828,333$0$0$No---------------------------
Dominik KubalikRed Wings (DET)LW301995-08-21CZEYes192 Lbs6 ft2NoNoN/ANoNo12025-08-10FalseFalsePro & Farm3,000,000$0$0$No---------------------------
Dylan CoghlanRed Wings (DET)D281998-02-19CANYes205 Lbs6 ft2NoNoN/ANoNo22024-09-08FalseFalsePro & Farm600,000$0$0$No600,000$-----------------No--------
Dylan GuentherRed Wings (DET)LW232003-04-10CANYes191 Lbs6 ft1NoNoAssign ManuallyNoNo22024-08-17FalseFalsePro & Farm894,167$0$0$No894,167$--------894,167$--------No--------
Elmer SoderblomRed Wings (DET)RW242001-07-05SWEYes246 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm878,333$0$0$No---------------------------
Fredrik KarlstromRed Wings (DET)C281998-01-12SWEYes194 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm750,000$0$0$No---------------------------
Gabriel FortierRed Wings (DET)LW262000-02-06CANYes172 Lbs5 ft10NoNoN/ANoNo32025-08-10FalseFalsePro & Farm575,000$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$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$0$0$No700,000$-----------------No--------
Jeffrey Truchon-VielRed Wings (DET)LW291997-01-28CANYes205 Lbs6 ft2NoNoTrade2024-12-22NoNo22024-09-18FalseFalsePro & Farm575,000$0$0$No575,000$--------575,000$--------No--------
Joe MorrowRed Wings (DET)D331992-12-09CANNo196 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,000,000$0$0$No---------------------------
Joel HoferRed Wings (DET)G252000-07-30CANYes179 Lbs6 ft5NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,500,000$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$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$0$0$No900,000$-----------------No--------
Justin BraunRed Wings (DET)D391987-02-10USANo208 Lbs6 ft2NoNoFree AgentNoNo22024-10-06FalseFalsePro & Farm1,500,000$0$0$No1,500,000$--------1,500,000$--------No--------
Justus AnnunenRed Wings (DET)G262000-03-11FINYes210 Lbs6 ft4NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,500,000$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$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$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$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$0$0$No600,000$-----------------No--------
Logan O'ConnorRed Wings (DET)RW291996-08-14CANYes175 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,500,000$0$0$No---------------------------
Madison BoweyRed Wings (DET)D311995-04-22CANYes198 Lbs6 ft2NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,000,000$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$0$0$No---------------------------
Noah OstlundRed Wings (DET)C222004-03-11SWEYes165 Lbs5 ft11NoNoAssign ManuallyNoNo32025-09-06FalseFalsePro & Farm886,667$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$0$0$No---------------------------
Par LindholmRed Wings (DET)LW341991-10-05SWEYes183 Lbs5 ft11NoNoFree AgentNoNo32025-09-21FalseFalsePro & Farm575,000$0$0$No575,000$575,000$-------575,000$575,000$-------NoNo-------
Pius SuterRed Wings (DET)C301996-05-24SUIYes179 Lbs5 ft11NoNoN/ANoNo12024-09-08FalseFalsePro & Farm2,500,000$0$0$No---------------------------
Sami NikuRed Wings (DET)D291996-10-10FINYes176 Lbs6 ft1NoNoN/ANoNo22025-08-10FalseFalsePro & Farm575,000$0$0$No575,000$--------575,000$--------No--------
Scott ReedyRed Wings (DET)C271999-04-04USAYes214 Lbs6 ft2NoNoN/ANoNo32025-08-10FalseFalsePro & Farm575,000$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$0$0$No1,500,000$-----------------No--------
Urho VaakanainenRed Wings (DET)D271999-01-01FINYes205 Lbs6 ft2NoNoN/ANoNo32025-08-10FalseFalsePro & Farm1,500,000$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$0$0$No800,000$-----------------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3627.72197 Lbs6 ft22.031,112,120$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dominik KubalikPius SuterLogan O'Connor35122
2Dylan GuentherTeddy BluegerOskar Lindblom35122
3A.J. GreerJohn HaydenWade Allison25122
4Cole KoepkeLogan BrownElmer Soderblom5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCam York35122
2Urho VaakanainenJamie Drysdale35122
3Justin BraunMadison Bowey30122
4Juuso ValimakiCam York0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dominik KubalikPius SuterLogan O'Connor60122
2Dylan GuentherTeddy 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 LindblomDylan Guenther40122
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 LindblomDylan Guenther40122
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
A.J. Greer, Wade Allison, Cole KoepkeA.J. Greer, Wade AllisonCole Koepke
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Justin Braun, Madison Bowey, Urho VaakanainenJustin BraunMadison Bowey, Urho Vaakanainen
Tirs de pénalité
Logan O'Connor, Dominik Kubalik, Oskar Lindblom, Dylan Guenther, Pius Suter
Gardien
#1 : Joel Hofer, #2 : Justus Annunen
Lignes d’attaque personnalisées en prolongation
Logan O'Connor, Dominik Kubalik, Oskar Lindblom, Dylan Guenther, Pius Suter, Teddy Blueger, A.J. Greer, Wade Allison, Cole Koepke, Elmer Soderblom
Lignes de défense personnalisées en prolongation
Juuso Valimaki, Cam York, Urho Vaakanainen, Jamie Drysdale, Justin Braun


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
1Canadiens624000001825-7321000001011-130300000814-640.33318314900683118171525531877110414827518.52%22577.27%07814653.42%7814753.06%519653.13%133781265510251R5
Total624000001825-7321000001011-130300000814-640.33318314900683118171525531877110414827518.52%22577.27%07814653.42%7814753.06%519653.13%133781265510251
_Since Last GM Reset624000001825-7321000001011-130300000814-640.33318314900683118171525531877110414827518.52%22577.27%07814653.42%7814753.06%519653.13%133781265510251
_Vs Conference624000001825-7321000001011-130300000814-640.33318314900683118171525531877110414827518.52%22577.27%07814653.42%7814753.06%519653.13%133781265510251
_Vs Division624000001825-7321000001011-130300000814-640.33318314900683118171525531877110414827518.52%22577.27%07814653.42%7814753.06%519653.13%133781265510251

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
64L21831491811877110414800
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
62400001825
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
32100001011
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3030000814
Derniers 10 matchs
WLOTWOTL SOWSOL
240000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
27518.52%22577.27%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
71525536831
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
7814653.42%7814753.06%519653.13%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
133781265510251


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
11Red Wings4Canadiens5LR5Sommaire du match
39Red Wings1Canadiens3LSommaire du match
517Canadiens4Red Wings5WXR5Sommaire du match
725Canadiens1Red Wings3WSommaire du match
933Red Wings3Canadiens6LR5Sommaire du match
1141Canadiens6Red Wings2LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4525
Assistance4,9963,000
Assistance PCT83.27%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
38 2665 - 88.84% 134,919$404,757$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 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$ 0$ 0 0

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




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
Saison régulière
1982353504233260263-3411915031211451261941162001112115137-2289260435695227191917264188487386935260187059020112354418.72%2074180.19%21057205151.54%970198848.79%611126648.26%1803107417607191392699
2082343303336272284-1241181601123143141241161702213129143-14892724707421078101879259287591777664262685383620132303816.52%2304580.43%2997198450.25%899189447.47%617128248.13%1775105917977271402699
Total Saison régulière164696807569532547-15823731042442882672182323703325244280-361785329051437321491921781652331759179016459952271723142640244658217.63%4378680.32%42054403550.90%1869388248.15%1228254848.19%357921343557144727941398
Séries éliminatoires
20624000001825-7321000001011-130300000814-6418314900683118171525531877110414827518.52%22577.27%07814653.42%7814753.06%519653.13%133781265510251
Total Séries éliminatoires624000001825-7321000001011-130300000814-6418314900683118171525531877110414827518.52%22577.27%07814653.42%7814753.06%519653.13%133781265510251

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