Connexion

Red Wings
GP: 60 | W: 29 | L: 28 | OTL: 3 | P: 61
GF: 168 | GA: 185 | PP%: 18.78% | PK%: 80.65%
DG: | Morale : 40 | Moyenne d’équipe : 68
Prochains matchs #950 vs Oilers
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Centre de jeu
Red Wings
29-28-3, 61pts
2
FINAL
4 Coyotes
24-31-4, 52pts
Team Stats
L2StreakW2
14-12-3Home Record12-15-2
15-16-0Away Record12-16-2
4-5-1Last 10 Games5-4-1
2.80Buts par match 2.78
3.08Buts contre par match 3.36
18.78%Pourcentage en avantage numérique18.03%
80.65%Pourcentage en désavantage numérique71.98%
Golden Knights
29-20-8, 66pts
2
FINAL
1 Red Wings
29-28-3, 61pts
Team Stats
SOL1StreakL2
17-9-4Home Record14-12-3
12-11-4Away Record15-16-0
5-4-1Last 10 Games4-5-1
2.89Buts par match 2.80
2.77Buts contre par match 3.08
24.23%Pourcentage en avantage numérique18.78%
76.74%Pourcentage en désavantage numérique80.65%
Oilers
35-21-4, 74pts
2022-10-10
Red Wings
29-28-3, 61pts
Statistiques d’équipe
W7SéquenceL2
17-8-4Fiche domicile14-12-3
18-13-0Fiche visiteur15-16-0
8-1-110 derniers matchs4-5-1
3.12Buts par match 2.80
2.67Buts contre par match 2.80
25.00%Pourcentage en avantage numérique18.78%
82.79%Pourcentage en désavantage numérique80.65%
Red Wings
29-28-3, 61pts
2022-10-12
Flyers
26-25-7, 59pts
Statistiques d’équipe
L2SéquenceL3
14-12-3Fiche domicile15-12-2
15-16-0Fiche visiteur11-13-5
4-5-110 derniers matchs4-4-2
2.80Buts par match 3.02
3.08Buts contre par match 3.02
18.78%Pourcentage en avantage numérique19.28%
80.65%Pourcentage en désavantage numérique79.17%
Lightning
30-24-8, 68pts
2022-10-14
Red Wings
29-28-3, 61pts
Statistiques d’équipe
L1SéquenceL2
14-13-2Fiche domicile14-12-3
16-11-6Fiche visiteur15-16-0
5-3-210 derniers matchs4-5-1
2.77Buts par match 2.80
2.65Buts contre par match 2.80
20.30%Pourcentage en avantage numérique18.78%
80.95%Pourcentage en désavantage numérique80.65%
Meneurs d'équipe
Jakub VranaButs
Jakub Vrana
20
Moritz SeiderPasses
Moritz Seider
33
Jakub VranaPoints
Jakub Vrana
44
Jakub VranaPlus/Moins
Jakub Vrana
5
Alex NedeljkovicVictoires
Alex Nedeljkovic
25
Calvin PickardPourcentage d’arrêts
Calvin Pickard
0.968

Statistiques d’équipe
Buts pour
168
2.80 GFG
Tirs pour
1737
28.95 Avg
Pourcentage en avantage numérique
18.8%
34 GF
Début de zone offensive
40.9%
Buts contre
185
3.08 GAA
Tirs contre
1817
30.28 Avg
Pourcentage en désavantage numérique
80.6%
30 GA
Début de la zone défensive
41.0%
Informations de l'équipe

Directeur général
EntraîneurJeff Blashill
DivisionAtlantic
ConférenceEastern
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

NomLittle Caesars Arena
Capacité19,515
Assistance17,150
Billets de saison7,806


Informations de la formation

Équipe Pro25
Équipe Mineure15
Limite contact 40 / 20
Espoirs0


Plafond salarial

Cap Salarial de la Saison estimé56,733,514$
Plafond salarial disponible33,266,486$
Valeur du plafond salarial spécial0$
Joueurs Inclus dans le plafond salarial25


Finance

Revenu annuel à ce jour44,000,477$
Dépenses annuelles à ce jour39,264,154$
Revenus de la saison estimés18,207,094$
Dépenses de la saison estimées17,469,360$
Compte bancaire actuel13,552,900$
Compte bancaire projeté13,788,538$


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
1Dylan LarkinX99.0065367885779088798680786779718479407402526,100,000$
2Jakub VranaX99.0058359082748581775975836179697280407202625,250,000$
3Lucas RaymondX99.006033958071918477557877617963679040700203925,000$
4Robby FabbriX96.0071378576698883767972776177697377407002612,950,000$
5Pius SuterX100.0057349373678790748372717373687040406902623,250,000$
6Sam GagnerX100.006137896971849071806865737387755140680321850,000$
7Michael RasmussenX100.0078397667958589668165667066656783406702331,460,000$
8Filip ZadinaX100.005835927877868976567266557665668540670221894,167$
9Oskar SundqvistX100.0070408566858483647868637865717351406702822,750,000$
10Joe VelenoX100.007538906880839565826364676763657740660221894,167$
11Alexander VolkovXX100.007548828181767763606460656765656940660241925,000$
12Carter RowneyX100.007736926183807461776462806275742540660331825,000$
13Adam ErneX100.0081718667808390626163665665697165406502722,100,000$
14Riley BarberX100.006438856274807862666063576771724640620281800,000$
15Moritz SeiderX99.007838907687938277308666875664698740730213863,333$
16Filip HronekX99.0062348974729383733080617153686766406802434,400,000$
17Danny DeKeyserX100.0064368862818987623074598351787425406703215,000,000$
18Marc StaalX100.0070388563888687613073607650907843406703512,000,000$
19Gustav LindstromX100.006435866678878164307456724965667140650231850,000$
20Jordan OesterleX100.0059348967718983653071566853727434406402921,350,000$
Rayé
1Tyler BertuzziX96.0071587973779081756078846973707157407202724,750,000$
2Jake WalmanX100.006437946983848067306560655267685940640261725,000$
Équipe Mineure
1Taro HiroseX100.006135946663868369716860556468694140630251850,000$
2Kyle CriscuoloX100.006435776669837664746861556471733440630302750,000$
3Turner ElsonX100.0071389258738586606960615859717334406202910$
4Chase PearsonX99.006339896185777860735958596366685440610241874,125$
5Givani SmithX97.008583605784747856555758546165666940590242750,000$
6Adam JohnsonX100.0060388557698280576160595357697035405902710$
7Alex KileX100.0064369555737162545853575155697035405702710$
8Olli JuoleviX99.006739916678807166306565625565678340630241750,000$
9Dan RenoufX100.0073457459837684593068626153697135406202810$
10Jared McIsaacX100.006739866478718663306260584563657540620222764,167$
11Ryan MurphyX99.006139796569768366306560584970726840620291800,000$
12Brian LashoffX100.007742835786658857305657574673782640610311750,000$
13Wyatt NewpowerX100.007334755783658157305857624566685140600242800,000$
14Donovan SebrangoX100.006638875675638455305453494561636840570203850,833$
15Mitchell StephensX83.236234886371777262836658675765667340620251737,005$
MOYENNE D’ÉQUIPE99.03674086677782826555676364616970584065
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 Nedeljkovic97.569294918091899090889291697671407202623,000,000$
2Thomas Greiss100.008685798485848685838685829148406903613,600,000$
Rayé
1Calvin Pickard100.00747978807373757372747372845740630301800,000$
Équipe Mineure
MOYENNE D’ÉQUIPE99.0084868381838284838184837484594068
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jeff Blashill79817984726778USA4800$


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
1Jakub VranaRed WingsLW4120244458024631704212511.76%793222.74538301130002833322.7411700000.9401000711
2Moritz SeiderRed WingsD5053338-21500110999027595.56%88124024.80189581450000100100.00%000000.6100000041
3Lucas RaymondRed WingsLW60181836-76028881715112110.53%8109518.2514518680003991318.2510000000.6603000313
4Danny DeKeyserRed WingsD6062935324070767619537.89%93124320.733912351450000109020.00%000000.5600000122
5Robby FabbriRed WingsC4116193541006197122298513.11%383320.3415615730002445120.3494400000.8402000213
6Pius SuterRed WingsC49151833-92022871474711110.20%882516.8544819740000233016.8595300000.8002000123
7Filip HronekRed WingsD5362531-1418042567729457.79%77130924.71235441500110118100.00%000000.4700000013
8Tyler BertuzziRed WingsLW50161531-742101038216342919.82%8118723.755272713200021083123.7523700000.5202002150
9Filip ZadinaRed WingsRW60141630-46026641253610111.20%6117319.5544828165000002119.558300000.5111000121
10Dylan LarkinRed WingsC3013162918049105122359410.66%674124.7114523921015854124.7196500110.7800000421
11Marc StaalRed WingsD6052429-2300100377319396.85%75127621.28268321540000110210.00%000000.4500000122
12Gustav LindstromRed WingsD532161813208327216229.52%5579415.00011515000037000.00%000000.4500000002
13Sam GagnerRed WingsC365712-122016605520489.09%1048913.601237560000151013.6056400000.4912000100
14Michael RasmussenRed WingsC605510-9405145518279.80%74026.70224619000021106.7040600000.5001000001
15Alexander VolkovRed WingsLW/RW233710019545184413356.82%243218.81123261000000018.811900000.4600010002
16Jordan OesterleRed WingsD412810-510031281631212.50%2551612.6100025011012000.00%000000.3900000000
17Oskar SundqvistRed WingsC606410-128019757515398.00%114968.2800001000010008.2847300000.4000000110
18Jake WalmanRed WingsD573710-51605137326259.38%4279814.02101617000037000.00%000000.2500000010
19Riley BarberRed WingsRW55257-711571164515354.44%693016.92033886000000116.925100000.1500100010
20Adam ErneRed WingsLW35314-5402392910910.34%33449.840000000004009.842100000.2300000001
21Joe VelenoRed WingsC601234202171314.29%0460.7801102000114000.782500001.2800000000
22Givani SmithGriffins (DET)RW42022-122809510233160.00%560214.3600001000000014.364700000.0700000000
23Carter RowneyRed WingsC600111002102040.00%0350.5900001000015000.593000000.5600000000
24Olli JuoleviGriffins (DET)D10011-200131000.00%3414.110000000001000.00%000000.4900000000
Statistiques d’équipe totales ou en moyenne1146166303469-1143402011251193173747611999.56%5481779215.533463973651586123151055271449.37%503500110.53214112232626
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 NedeljkovicRed Wings49252210.8983.1327616014414090211.0004491311
2Thomas GreissRed Wings184620.8992.8380700383760200.900101149020
3Calvin PickardRed Wings20000.9681.1552001310000.00%0010000
Statistiques d’équipe totales ou en moyenne69292830.8993.0336216018318160410.929146060331


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 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
Adam ErneRed WingsLW271995-04-20No211 Lbs6 ft1NoNoNo2Pro & Farm2,100,000$640,107$2,100,000$640,107$No2,100,000$Lien / Lien NHL
Alex NedeljkovicRed WingsG261996-01-07No203 Lbs6 ft0NoNoNo2Pro & Farm3,000,000$914,439$3,000,000$914,439$No3,000,000$Lien / Lien NHL
Alexander VolkovRed WingsLW/RW241997-08-02No192 Lbs6 ft1NoNoNo1Pro & Farm925,000$281,952$925,000$281,952$NoLien / Lien NHL
Calvin PickardRed WingsG301992-04-15No210 Lbs6 ft1NoNoNo1Pro & Farm800,000$243,850$800,000$243,850$NoLien / Lien NHL
Carter RowneyRed WingsC331989-05-10No208 Lbs6 ft2NoNoNo1Pro & Farm825,000$251,471$825,000$251,471$NoLien / Lien NHL
Danny DeKeyserRed WingsD321990-03-07No183 Lbs6 ft3NoNoNo1Pro & Farm5,000,000$1,524,064$5,000,000$1,524,064$NoLien / Lien NHL
Dylan LarkinRed WingsC251996-07-30No198 Lbs6 ft1NoNoNo2Pro & Farm6,100,000$1,859,358$6,100,000$1,859,358$No6,100,000$Lien / Lien NHL
Filip HronekRed WingsD241997-11-02No188 Lbs6 ft0NoNoNo3Pro & Farm4,400,000$1,341,176$4,400,000$1,341,176$No4,400,000$4,400,000$Lien / Lien NHL
Filip ZadinaRed WingsRW221999-11-27No197 Lbs6 ft0NoNoNo1Pro & Farm894,167$272,554$894,167$272,554$NoLien / Lien NHL
Gustav LindstromRed WingsD231998-10-20No183 Lbs6 ft2NoNoNo1Pro & Farm850,000$259,091$850,000$259,091$NoLien / Lien NHL
Jake WalmanRed WingsD261996-02-20No215 Lbs6 ft2NoNoNo1Pro & Farm725,000$220,989$725,000$220,989$NoLien / Lien NHL
Jakub VranaRed WingsLW261996-02-28No196 Lbs6 ft0NoNoNo2Pro & Farm5,250,000$1,600,267$5,250,000$1,600,267$No5,250,000$Lien / Lien NHL
Joe VelenoRed WingsC222000-01-13No206 Lbs6 ft1NoNoNo1Pro & Farm894,167$272,554$894,167$272,554$NoLien / Lien NHL
Jordan OesterleRed WingsD291992-06-25No188 Lbs6 ft0NoNoNo2Pro & Farm1,350,000$411,497$1,350,000$411,497$No1,350,000$Lien / Lien NHL
Lucas RaymondRed WingsLW202002-03-28No182 Lbs5 ft11NoNoNo3Pro & Farm925,000$281,952$925,000$281,952$No925,000$925,000$Lien
Marc StaalRed WingsD351987-01-13No208 Lbs6 ft4NoNoNo1Pro & Farm2,000,000$609,626$2,000,000$609,626$NoLien / Lien NHL
Michael RasmussenRed WingsC231999-04-17No210 Lbs6 ft6NoNoNo3Pro & Farm1,460,000$445,027$1,460,000$445,027$No1,460,000$1,460,000$Lien / Lien NHL
Moritz SeiderRed WingsD212001-04-06No197 Lbs6 ft4NoNoNo3Pro & Farm863,333$263,155$863,333$263,155$No863,333$863,333$Lien / Lien NHL
Oskar SundqvistRed WingsC281994-03-23No208 Lbs6 ft3NoNoNo2Pro & Farm2,750,000$838,235$2,750,000$838,235$No2,750,000$Lien / Lien NHL
Pius SuterRed WingsC261996-05-24No174 Lbs5 ft11NoNoNo2Pro & Farm3,250,000$990,642$3,250,000$990,642$No3,250,000$Lien / Lien NHL
Riley BarberRed WingsRW281994-02-07No199 Lbs6 ft0NoNoNo1Pro & Farm800,000$243,850$800,000$243,850$NoLien / Lien NHL
Robby FabbriRed WingsC261996-01-22No183 Lbs5 ft11NoNoNo1Pro & Farm2,950,000$899,198$2,950,000$899,198$NoLien / Lien NHL
Sam GagnerRed WingsC321989-08-10No197 Lbs5 ft11NoNoNo1Pro & Farm850,000$259,091$850,000$259,091$NoLien / Lien NHL
Thomas GreissRed WingsG361986-01-29No219 Lbs6 ft2NoNoNo1Pro & Farm3,600,000$1,097,326$3,600,000$1,097,326$NoLien / Lien NHL
Tyler BertuzziRed WingsLW271995-02-24No197 Lbs6 ft1NoNoNo2Pro & Farm4,750,000$1,447,861$4,750,000$1,447,861$No4,750,000$Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2526.84198 Lbs6 ft11.642,292,467$

Somme salaire 1e année Somme salaire 2e année Somme salaire 3e année Somme salaire 4e année Somme salaire 5e année
57,311,667$36,198,333$7,648,333$0$0$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jakub VranaDylan LarkinFilip Zadina40122
2Lucas RaymondRobby FabbriAlexander Volkov30122
3Adam ErnePius SuterRiley Barber20122
4Dylan LarkinSam GagnerJakub Vrana10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Moritz SeiderFilip Hronek40122
2Danny DeKeyserMarc Staal30122
3Gustav LindstromJordan Oesterle20122
4Moritz SeiderFilip Hronek10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jakub VranaDylan LarkinFilip Zadina60122
2Lucas RaymondRobby FabbriAlexander Volkov40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Moritz SeiderFilip Hronek60122
2Danny DeKeyserMarc Staal40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Dylan LarkinJakub Vrana60122
2Robby FabbriLucas Raymond40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Moritz SeiderFilip Hronek60122
2Danny DeKeyserMarc Staal40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Dylan Larkin60122Moritz SeiderFilip Hronek60122
2Jakub Vrana40122Danny DeKeyserMarc Staal40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dylan LarkinJakub Vrana60122
2Robby FabbriLucas Raymond40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Moritz SeiderFilip Hronek60122
2Danny DeKeyserMarc Staal40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jakub VranaDylan LarkinFilip ZadinaMoritz SeiderFilip Hronek
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jakub VranaDylan LarkinFilip ZadinaMoritz SeiderFilip Hronek
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Oskar Sundqvist, Michael Rasmussen, Joe VelenoOskar Sundqvist, Michael RasmussenJoe Veleno
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Gustav Lindstrom, Jordan Oesterle, Danny DeKeyserGustav LindstromJordan Oesterle, Danny DeKeyser
Tirs de pénalité
Dylan Larkin, Jakub Vrana, Robby Fabbri, Lucas Raymond, Pius Suter
Gardien
#1 : Alex Nedeljkovic, #2 : Thomas Greiss
Lignes d’attaque personnalisées en prolongation
Dylan Larkin, Jakub Vrana, Robby Fabbri, Lucas Raymond, Pius Suter, Sam Gagner, Sam Gagner, Oskar Sundqvist, Michael Rasmussen, Filip Zadina, Alexander Volkov
Lignes de défense personnalisées en prolongation
Moritz Seider, Filip Hronek, Danny DeKeyser, Marc Staal, Gustav Lindstrom


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
1Avalanche10001000321000000000001000100032121.00036900101134991243811024300.00%000.00%01051204051.52%1002204748.95%43390347.95%2416267126
2BlackHawks2020000048-41010000012-11010000036-300.000471100310046151912078271030600.00%5180.00%01051204051.52%1002204748.95%43390347.95%402754142412
3Blue Jackets2010010047-31000010023-11010000024-210.2504711002110551026190701316414125.00%6183.33%01051204051.52%1002204748.95%43390347.95%493447142412
4Blues11000000532110000005320000000000021.0005914002210331710602696163266.67%30100.00%01051204051.52%1002204748.95%43390347.95%2315227147
5Bruins31200000810-22020000047-31100000043120.33381422003320983331340862119491200.00%7185.71%01051204051.52%1002204748.95%43390347.95%694973223617
6Canadiens523000001013-3321000007522020000038-540.400101929006220158575150016760319912325.00%13192.31%01051204051.52%1002204748.95%43390347.95%11380125346030
7Canucks1010000025-3000000000001010000025-300.000246002000298912024126256116.67%3166.67%01051204051.52%1002204748.95%43390347.95%2720206125
8Coyotes2010000169-31000000145-11010000024-210.2506111700222073242124848101139100.00%220.00%01051204051.52%1002204748.95%43390347.95%533845142613
9Devils11000000523110000005230000000000021.000591400212034178903186264250.00%30100.00%01051204051.52%1002204748.95%43390347.95%2215256116
10Ducks210001007611000010023-11100000053230.7507111800421064202420047178366233.33%3166.67%01051204051.52%1002204748.95%43390347.95%432948152814
11Flames1010000023-1000000000001010000023-100.000235001010216780309222200.00%10100.00%01051204051.52%1002204748.95%43390347.95%2215256125
12Golden Knights2020000025-31010000012-11010000013-200.000246102000461714150592114357114.29%70100.00%01051204051.52%1002204748.95%43390347.95%432951152412
13Hurricaines1010000005-51010000005-50000000000000.000000000000178450378819400.00%4250.00%01051204051.52%1002204748.95%43390347.95%2416227136
14Islanders311010009901010000013-22100100086240.66791625002241792321332883222608225.00%10280.00%01051204051.52%1002204748.95%43390347.95%664473224119
15Jets1010000035-2000000000001010000035-200.000369002100274914022116224125.00%3166.67%01051204051.52%1002204748.95%43390347.95%2316246126
16Kings2010001069-3100000105411010000015-420.5006915002301642234576514143610550.00%7442.86%01051204051.52%1002204748.95%43390347.95%523947132412
17Kraken320010001174210010007521100000042261.00011213200631110134412248524186014214.29%8187.50%01051204051.52%1002204748.95%43390347.95%755368223619
18Lightning30101010871100010002112010001066040.667810180032127628232011762716497114.29%8187.50%01051204051.52%1002204748.95%43390347.95%684682233818
19Maple Leafs422000001012-22110000045-12110000067-140.5001018280027109834382601164312698112.50%6266.67%01051204051.52%1002204748.95%43390347.95%8557104284924
20Oilers21100000853000000000002110000085320.50081624003230492211160641420256116.67%10280.00%01051204051.52%1002204748.95%43390347.95%402555152411
21Panthers3120000068-21010000013-22110000055020.33361218000330691630230102221247600.00%6183.33%01051204051.52%1002204748.95%43390347.95%674675213617
22Penguins21100000810-21010000036-31100000054120.50081321002240632017260782112538225.00%6183.33%01051204051.52%1002204748.95%43390347.95%453249132412
23Predators22000000642110000002111100000043141.0006111700204064192322035100311100.00%000.00%01051204051.52%1002204748.95%43390347.95%544041142412
24Rangers11000000431110000004310000000000021.00048120021103612141002756193133.33%30100.00%01051204051.52%1002204748.95%43390347.95%2317247125
25Sabres4220000014131211000007612110000077040.500142842004550116342458012438267714321.43%13376.92%11051204051.52%1002204748.95%43390347.95%987091285025
26Senators32100000770110000003122110000046-240.66771219001240873323310992431497114.29%12283.33%01051204051.52%1002204748.95%43390347.95%715071203718
27Sharks11000000422110000004220000000000021.000481200211039161112028134264250.00%20100.00%01051204051.52%1002204748.95%43390347.95%2316246126
28Wild211000006601010000024-21100000042220.5006111700312061261619067241041100.00%40100.00%01051204051.52%1002204748.95%43390347.95%473347132513
Total60232804221168185-17291112022117681-53112160201092104-12610.508168303471106649476173758456856336181754834611251813418.78%1553080.65%11051204051.52%1002204748.95%43390347.95%14029801472434752374
_Since Last GM Reset60232804221168185-17291112022117681-53112160201092104-12610.508168303471106649476173758456856336181754834611251813418.78%1553080.65%11051204051.52%1002204748.95%43390347.95%14029801472434752374
_Vs Conference3514170211093106-131879011004350-71778010105056-6350.50093166259002931303986325310344131101322217657971717.53%971782.47%11051204051.52%1002204748.95%43390347.95%805562868252437215
_Vs Division251013010106370-7125601000282801357000103542-7240.480631131760019241827022352202421177023514743966913.64%651183.08%11051204051.52%1002204748.95%43390347.95%574401624180310153

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6061L216830347117371817548346112510
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6023284221168185
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
29111222117681
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
311216201092104
Derniers 10 matchs
WLOTWOTL SOWSOL
450100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1813418.78%1553080.65%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
584568563366649476
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
1051204051.52%1002204748.95%43390347.95%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
14029801472434752374


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 - 2022-05-318Canadiens1Red Wings3BWSommaire du match
3 - 2022-06-0221Red Wings2Canadiens4ALSommaire du match
5 - 2022-06-0436Red Wings4Bruins3AWSommaire du match
6 - 2022-06-0547Red Wings4Islanders3AWSommaire du match
8 - 2022-06-0763Senators1Red Wings3BWSommaire du match
10 - 2022-06-0980Red Wings7Oilers2AWSommaire du match
12 - 2022-06-1195Bruins3Red Wings1BLSommaire du match
15 - 2022-06-14109Red Wings4Senators1AWSommaire du match
17 - 2022-06-16124Sabres5Red Wings2BLSommaire du match
19 - 2022-06-18139Red Wings4Maple Leafs1AWSommaire du match
22 - 2022-06-21156Maple Leafs3Red Wings0BLSommaire du match
25 - 2022-06-24177Red Wings5Sabres3AWSommaire du match
27 - 2022-06-26188Panthers3Red Wings1BLSommaire du match
30 - 2022-06-29214Lightning1Red Wings2BWXSommaire du match
32 - 2022-07-01227Red Wings4Islanders3AWXSommaire du match
33 - 2022-07-02232Red Wings3Panthers1AWSommaire du match
36 - 2022-07-05254Kraken3Red Wings4BWXSommaire du match
40 - 2022-07-09275Maple Leafs2Red Wings4BWSommaire du match
43 - 2022-07-12296Kraken2Red Wings3BWSommaire du match
45 - 2022-07-14312Red Wings2Panthers4ALSommaire du match
47 - 2022-07-16331Devils2Red Wings5BWSommaire du match
49 - 2022-07-18345Red Wings5Penguins4AWSommaire du match
51 - 2022-07-20361Red Wings4Wild2AWSommaire du match
53 - 2022-07-22375Sharks2Red Wings4BWSommaire du match
55 - 2022-07-24389Red Wings1Canadiens4ALSommaire du match
57 - 2022-07-26405Coyotes5Red Wings4BLXXSommaire du match
59 - 2022-07-28418Red Wings4Kraken2AWSommaire du match
61 - 2022-07-30433Penguins6Red Wings3BLSommaire du match
63 - 2022-08-01441Red Wings3Jets5ALSommaire du match
65 - 2022-08-03458Red Wings1Golden Knights3ALSommaire du match
67 - 2022-08-05469Red Wings2Flames3ALSommaire du match
68 - 2022-08-06479Hurricaines5Red Wings0BLSommaire du match
71 - 2022-08-09502BlackHawks2Red Wings1BLSommaire du match
73 - 2022-08-11515Red Wings1Oilers3ALSommaire du match
75 - 2022-08-13531Red Wings0Senators5ALSommaire du match
77 - 2022-08-15543Kings4Red Wings5BWXXSommaire du match
80 - 2022-08-18563Red Wings3Lightning4ALSommaire du match
82 - 2022-08-20573Rangers3Red Wings4BWSommaire du match
85 - 2022-08-23594Red Wings2Blue Jackets4ALSommaire du match
86 - 2022-08-24605Blues3Red Wings5BWSommaire du match
90 - 2022-08-28632Bruins4Red Wings3BLSommaire du match
93 - 2022-08-31656Red Wings2Sabres4ALSommaire du match
95 - 2022-09-02667Predators1Red Wings2BWSommaire du match
97 - 2022-09-04686Red Wings2Canucks5ALSommaire du match
98 - 2022-09-05696Red Wings3BlackHawks6ALSommaire du match
100 - 2022-09-07703Canadiens2Red Wings3BWSommaire du match
103 - 2022-09-10725Red Wings3Avalanche2AWXSommaire du match
104 - 2022-09-11733Blue Jackets3Red Wings2BLXSommaire du match
107 - 2022-09-14757Red Wings2Maple Leafs6ALSommaire du match
108 - 2022-09-15766Canadiens2Red Wings1BLSommaire du match
111 - 2022-09-18789Sabres1Red Wings5BWSommaire du match
113 - 2022-09-20807Red Wings5Ducks3AWSommaire du match
114 - 2022-09-21813Red Wings4Predators3AWSommaire du match
116 - 2022-09-23830Islanders3Red Wings1BLSommaire du match
118 - 2022-09-25848Red Wings1Kings5ALSommaire du match
120 - 2022-09-27857Wild4Red Wings2BLSommaire du match
124 - 2022-10-01887Ducks3Red Wings2BLXSommaire du match
126 - 2022-10-03899Red Wings3Lightning2AWXXSommaire du match
128 - 2022-10-05913Red Wings2Coyotes4ALSommaire du match
129 - 2022-10-06924Golden Knights2Red Wings1BLSommaire du match
133 - 2022-10-10950Oilers-Red Wings-
135 - 2022-10-12972Red Wings-Flyers-
137 - 2022-10-14982Lightning-Red Wings-
139 - 2022-10-16998Red Wings-Blues-
141 - 2022-10-181008Red Wings-Sharks-
143 - 2022-10-201020Stars-Red Wings-
145 - 2022-10-221037Red Wings-Devils-
147 - 2022-10-241049Jets-Red Wings-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
152 - 2022-10-291081Senators-Red Wings-
154 - 2022-10-311102Avalanche-Red Wings-
156 - 2022-11-021115Red Wings-Bruins-
159 - 2022-11-051138Flames-Red Wings-
161 - 2022-11-071149Red Wings-Stars-
163 - 2022-11-091167Red Wings-Capitals-
165 - 2022-11-111176Canucks-Red Wings-
167 - 2022-11-131187Red Wings-Hurricaines-
169 - 2022-11-151205Red Wings-Rangers-
170 - 2022-11-161212Capitals-Red Wings-
173 - 2022-11-191242Flyers-Red Wings-
178 - 2022-11-241265Islanders-Red Wings-
180 - 2022-11-261281Red Wings-Islanders-
185 - 2022-12-011308Panthers-Red Wings-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité60005000351540001000
Prix des billets100603525200
Assistance163,393131,35471,094103,41128,095
Attendance PCT93.90%90.59%69.74%89.15%96.88%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
12 17150 - 87.88% 1,517,258$44,000,477$19515100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineursValeur du plafond salarial spécial
39,264,154$ 57,311,667$ 57,311,667$ 0$ 0$
Plafond salarial par jourPlafond salarial à ce jourTaxe de luxe totaleJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
306,480$ 39,264,154$ 0$ 25 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
18,207,094$ 57 306,480$ 17,469,360$

Total de l’équipe estimé
Dépenses de la saison estimées Compte bancaire actuel Compte bancaire projeté
17,971,456$ 13,552,900$ 13,788,538$
Cap Salarial de la Saison estiméPlafond salarial disponiblePlafond salarial maximumAu dessus du plancher salarial
56,733,514$ 33,266,486$ 90,000,000$ 56,733,514$



Charte de profondeur

Ailier gaucheCentreAilier droit
Jakub VranaAGE:26PO:80OV:72
Tyler BertuzziAGE:27PO:57OV:72
Lucas RaymondAGE:20PO:90OV:70
Alexander VolkovAGE:24PO:69OV:66
Adam ErneAGE:27PO:65OV:65
Taro HiroseAGE:25PO:41OV:63
Adam JohnsonAGE:27PO:35OV:59
Alex KileAGE:27PO:35OV:57
Dylan LarkinAGE:25PO:79OV:74
Robby FabbriAGE:26PO:77OV:70
Pius SuterAGE:26PO:40OV:69
Sam GagnerAGE:32PO:51OV:68
Michael RasmussenAGE:23PO:83OV:67
Oskar SundqvistAGE:28PO:51OV:67
Joe VelenoAGE:22PO:77OV:66
Carter RowneyAGE:33PO:25OV:66
Kyle CriscuoloAGE:30PO:34OV:63
Mitchell StephensAGE:25PO:73OV:62
Turner ElsonAGE:29PO:34OV:62
Chase PearsonAGE:24PO:54OV:61
Filip ZadinaAGE:22PO:85OV:67
Alexander VolkovAGE:24PO:69OV:66
Riley BarberAGE:28PO:46OV:62
Givani SmithAGE:24PO:69OV:59

Défense #1Défense #2Gardien
Moritz SeiderAGE:21PO:87OV:73
Filip HronekAGE:24PO:66OV:68
Marc StaalAGE:35PO:43OV:67
Danny DeKeyserAGE:32PO:25OV:67
Gustav LindstromAGE:23PO:71OV:65
Jake WalmanAGE:26PO:59OV:64
Jordan OesterleAGE:29PO:34OV:64
Olli JuoleviAGE:24PO:83OV:63
Jared McIsaacAGE:22PO:75OV:62
Ryan MurphyAGE:29PO:68OV:62
Dan RenoufAGE:28PO:35OV:62
Brian LashoffAGE:31PO:26OV:61
Wyatt NewpowerAGE:24PO:51OV:60
Donovan SebrangoAGE:20PO:68OV:57
Alex NedeljkovicAGE:26PO:71OV:72
Thomas GreissAGE:36PO:48OV:69
Calvin PickardAGE:30PO:57OV:63

Espoirs

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
Espoir Nom de l’équipeAnnée de repêchage Choix total Information Lien

Choix au repêchage

Année R1R2R3R4R5
2
3
4
5
6




La base de données des nouvelles n'a pas été trouvée. Veuillez en créer une du STHS.




[2022-06-01 08:43:15] - New Record for Team's Most Shots Blocked (22) in 1 Game for Red Wings!
[2022-06-01 08:41:35] - Alexander Volkov was added to Red Wings.
[2022-06-01 08:41:31] - Adam Johnson was added to Red Wings.
[2022-06-01 08:41:26] - Alex Kile was added to Red Wings.
[2022-05-31 20:42:30] - New Record for Team's Most Shots (43) in 1 Game for Red Wings!
[2022-05-31 20:32:32] - New Record for Team's Most Shots (40) in 1 Game for Red Wings!
[2022-05-31 20:08:34] - New Record for Team's Most Points (21) in 1 Game for Red Wings!
[2022-05-31 20:08:34] - New Record for Team's Most Assists (14) in 1 Game for Red Wings!
[2022-05-31 20:08:34] - New Record for Team's Most Goals (7) in 1 Game for Red Wings!
[2022-05-31 20:08:34] - New Record for Team's Most Points (21) in 1 Game for Red Wings!
[2022-05-31 20:08:34] - New Record for Team's Most Assists (14) in 1 Game for Red Wings!
[2022-05-31 20:08:17] - New Record for Team's Most Points (12) in 1 Game for Red Wings!
[2022-05-31 20:08:17] - New Record for Team's Most Assists (8) in 1 Game for Red Wings!
[2022-05-31 20:08:12] - New Record for Team's Most Penalties Minutes (15) in 1 Game for Red Wings!
[2022-05-31 20:08:12] - New Record for Team's Most Points (11) in 1 Game for Red Wings!
[2022-05-31 20:08:12] - New Record for Team's Most Assists (7) in 1 Game for Red Wings!
[2022-05-31 20:08:12] - New Record for Team's Most Goals (4) in 1 Game for Red Wings!
[2022-05-31 19:50:02] - New Record for Team's Most Hits (28) in 1 Game for Red Wings!
[2022-05-31 19:50:02] - New Record for Team's Most Shots Blocked (19) in 1 Game for Red Wings!
[2022-05-31 19:50:02] - New Record for Team's Most Shots (38) in 1 Game for Red Wings!
[2022-05-31 19:50:02] - New Record for Team's Most Shots Blocked (19) in 1 Game for Red Wings!
[2022-05-31 19:49:54] - New Record for Team's Most Hits (18) in 1 Game for Red Wings!
[2022-05-31 19:49:54] - New Record for Team's Most Penalties Minutes (4) in 1 Game for Red Wings!
[2022-05-31 19:49:54] - New Record for Team's Most Shots Blocked (3) in 1 Game for Red Wings!
[2022-05-31 19:49:54] - New Record for Team's Most Shots (36) in 1 Game for Red Wings!
[2022-05-31 19:49:54] - New Record for Team's Most Points (9) in 1 Game for Red Wings!
[2022-05-31 19:49:54] - New Record for Team's Most Assists (6) in 1 Game for Red Wings!
[2022-05-31 19:49:54] - New Record for Team's Most Goals (3) in 1 Game for Red Wings!



[2022-06-01 10:16:29] Griffins lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:16:27] Game 930 - Unknown Player from Griffins is injured (Left Foot) and is out for 1 week.
[2022-06-01 10:16:25] Tyler Bertuzzi from Red Wings is back from Exhaustion.
[2022-06-01 10:16:25] Red Wings lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:16:21] Auto Lines Function has been run for Red Wings.
[2022-06-01 10:16:21] Auto Roster Partial Function has been run for Red Wings.
[2022-06-01 10:16:20] Both Red Wings and Griffins lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:16:17] Tyler Bertuzzi from Red Wings is injured from Exhaustion.
[2022-06-01 10:16:13] Alex Nedeljkovic from Red Wings is back from Back Spasms Injury.
[2022-06-01 10:16:13] Both Red Wings and Griffins lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:16:12] Game 903 - Mitchell Stephens from Griffins is injured (Left Hand) and is out for 3 weeks.
[2022-06-01 10:16:05] Taro Hirose from Griffins is back from Exhaustion.
[2022-06-01 10:16:05] Red Wings lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:56] Griffins lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:56] Taro Hirose from Griffins is injured from Exhaustion.
[2022-06-01 10:15:51] Griffins lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:47] Kyle Criscuolo from Griffins is back from Exhaustion.
[2022-06-01 10:15:47] Red Wings lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:42] Jordan Oesterle from Red Wings is back from Strained Right Elbow Injury.
[2022-06-01 10:15:42] Griffins lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:38] Kyle Criscuolo from Griffins is injured from Exhaustion.
[2022-06-01 10:15:38] Game 848 - Unknown Goalie from Griffins is injured (Bruised Left Arm) and is out for 1 week.
[2022-06-01 10:15:37] Red Wings lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:32] Griffins lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:27] Red Wings lines for next game are empty. Current rosters/lines are not erased.
[2022-06-01 10:15:24] Auto Lines Function has been run for Red Wings.
[2022-06-01 10:15:23] Jakub Vrana from Red Wings is back from Exhaustion.
[2022-06-01 10:15:23] Dylan Larkin from Red Wings is back from Exhaustion.



Mitchell Stephens est dehors pour 1 semaine à cause de Left Hand Injury.



Red Wings 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

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 (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