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LHSRSM


Red Wings
GP: 0 | W: 0 | L: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Patrick Auger | Morale : 99 | Moyenne d'Équipe : 66
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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 SP
1Auston Matthews (C)X100.00584289848791888385809167866568041750
2William Nylander (A)X100.00533988797485827871767763796772036700
3Tyler BertuzziXX100.00745678737783877256757459676966066690
4Nick SchmaltzXXX100.00523985777084737678796664776766026680
5Wayne SimmondsX100.00845561657779886856676659658073064660
6Mark JankowskiXX100.00554389668976846581636485657166027660
7Sam GagnerXXX100.00623986657273716678646361657971034640
8Garrett WilsonXX100.00775576628775786156606063597769033640
9Owen TippettXX100.00714589657982816459626366656164026640
10Vladimir SobotkaXX100.00793984617177736281605873618273036640
11Frederick GaudreauXX100.00583982637077756267615964627367042620
12Tye McGinnX100.00735781588789885651545759567868039620
13Dougie Hamilton (A)X100.00824374779887807630787975567374022730
14Darnell NurseX100.00865868709190926930796778556966028700
15Adam PelechX100.00854283648785816330735985527166036680
16Anton StralmanX100.00743989667087816530756085528477037680
17Oliver KylingtonX100.00583989657175776430626361546563026630
18Brandon ManningX100.00675075607873685930585561537868021610
19Mitch ReinkeX100.00534587626986886130605562456764022610
Rayé
1Marko DanoX100.00605281627377786354605861637166027620
2Stephen JohnsX100.00804675669172636530686467537568026660
MOYENNE D'ÉQUIPE100.0069468167798180675367656861726803466
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 SP
1John Gibson100.0092959382919092919092917377013750
2Chris Driedger100.0077727087767577767577767175026670
Rayé
MOYENNE D'ÉQUIPE100.008584828584838584838584727602071
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Stevens72776773807469CAN533500,000$


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
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


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 Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam PelechRed WingsD251994-08-16No218 Lbs6 ft3NoNoNo2Pro & Farm1,600,000$1,600,000$914,286$No1,600,000$Lien / Lien NHL
Anton StralmanRed WingsD331986-08-01No186 Lbs5 ft11NoNoNo3Pro & Farm5,500,000$5,500,000$3,142,857$No5,500,000$5,500,000$Lien / Lien NHL
Auston MatthewsRed WingsC221997-09-17No220 Lbs6 ft3NoNoNo5Pro & Farm11,634,000$11,634,000$6,648,000$No11,634,000$11,634,000$11,634,000$11,634,000$Lien / Lien NHL
Brandon ManningRed WingsD291990-06-04No205 Lbs6 ft1NoNoNo1Pro & Farm2,250,000$2,250,000$1,285,714$NoLien / Lien NHL
Chris DriedgerRed WingsG251994-05-18No205 Lbs6 ft4NoNoNo2Pro & Farm850,000$850,000$485,714$No850,000$Lien / Lien NHL
Darnell NurseRed WingsD241995-02-04No221 Lbs6 ft4NoNoNo1Pro & Farm3,200,000$3,200,000$1,828,571$NoLien / Lien NHL
Dougie HamiltonRed WingsD261993-06-17No229 Lbs6 ft6NoNoNo2Pro & Farm5,750,000$5,750,000$3,285,714$No5,750,000$Lien / Lien NHL
Frederick GaudreauRed WingsC/RW261993-05-01No179 Lbs6 ft0NoNoNo1Pro & Farm666,666$666,666$380,952$NoLien / Lien NHL
Garrett WilsonRed WingsLW/RW281991-03-16No218 Lbs6 ft3NoNoNo1Pro & Farm725,000$725,000$414,286$NoLien / Lien NHL
John GibsonRed WingsG261993-07-14No207 Lbs6 ft2NoNoNo8Pro & Farm6,400,000$6,400,000$3,657,143$No6,400,000$6,400,000$6,400,000$6,400,000$6,400,000$6,400,000$6,400,000$Lien / Lien NHL
Mark JankowskiRed WingsC/LW251994-09-13No212 Lbs6 ft4NoNoNo1Pro & Farm1,675,000$1,675,000$957,143$NoLien / Lien NHL
Marko DanoRed WingsLW241994-11-30No201 Lbs5 ft11NoNoNo1Pro & Farm800,000$800,000$457,143$NoLien / Lien NHL
Mitch ReinkeRed WingsD231996-02-04No181 Lbs5 ft11NoNoNo1Pro & Farm750,000$750,000$428,571$NoLien / Lien NHL
Nick SchmaltzRed WingsC/LW/RW231996-02-23No177 Lbs6 ft0NoNoNo7Pro & Farm5,850,000$5,850,000$3,342,857$No5,850,000$5,850,000$5,850,000$5,850,000$5,850,000$5,850,000$Lien / Lien NHL
Oliver KylingtonRed WingsD221997-05-19No183 Lbs6 ft0NoNoNo1Pro & Farm863,333$863,333$493,333$NoLien / Lien NHL
Owen TippettRed WingsLW/RW201999-02-16No207 Lbs6 ft1NoNoNo3Pro & Farm1,596,667$1,596,667$912,381$No1,596,667$1,596,667$Lien
Sam GagnerRed WingsC/LW/RW301989-08-10No200 Lbs5 ft11NoNoNo1Pro & Farm3,150,000$3,150,000$1,800,000$NoLien / Lien NHL
Stephen JohnsRed WingsD271992-04-18No225 Lbs6 ft4NoNoNo2Pro & Farm2,350,000$2,350,000$1,342,857$No2,350,000$Lien
Tye McGinnRed WingsLW291990-07-29No218 Lbs6 ft3NoNoNo1Pro & Farm650,000$650,000$371,429$NoLien / Lien NHL
Tyler BertuzziRed WingsLW/RW241995-02-24No199 Lbs6 ft1NoNoNo1Pro & Farm1,400,000$1,400,000$800,000$NoLien / Lien NHL
Vladimir SobotkaRed WingsC/LW321987-07-02No191 Lbs5 ft11NoNoNo1Pro & Farm3,500,000$3,500,000$2,000,000$NoLien / Lien NHL
Wayne SimmondsRed WingsRW311988-08-26No185 Lbs6 ft2NoNoNo1Pro & Farm0$0$NoLien / Lien NHL
William NylanderRed WingsRW231996-05-01No196 Lbs6 ft0NoNoNo5Pro & Farm6,962,366$6,962,366$3,978,495$No6,962,366$6,962,366$6,962,366$6,962,366$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2325.96203 Lbs6 ft22.262,961,871$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
68,123,032$48,493,033$37,943,033$30,846,366$30,846,366$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tyler BertuzziAuston MatthewsWilliam Nylander25122
2Mark JankowskiNick SchmaltzWayne Simmonds25122
3Owen TippettVladimir SobotkaSam Gagner25122
4Tye McGinnFrederick GaudreauGarrett Wilson25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dougie HamiltonDarnell Nurse30122
2Adam PelechAnton Stralman30122
3Oliver KylingtonBrandon Manning25122
4Dougie HamiltonDarnell Nurse15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tyler BertuzziAuston MatthewsWilliam Nylander60122
2Mark JankowskiNick SchmaltzWayne Simmonds40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dougie HamiltonDarnell Nurse60122
2Adam PelechAnton Stralman40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Auston MatthewsTyler Bertuzzi60122
2Nick SchmaltzWilliam Nylander40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dougie HamiltonDarnell Nurse60122
2Adam PelechAnton Stralman40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Auston Matthews60122Dougie HamiltonDarnell Nurse60122
2Nick Schmaltz40122Adam PelechAnton Stralman40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Auston MatthewsWilliam Nylander60122
2Nick SchmaltzTyler Bertuzzi40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dougie HamiltonDarnell Nurse60122
2Adam PelechAnton Stralman40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tyler BertuzziAuston MatthewsWilliam NylanderDougie HamiltonDarnell Nurse
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tyler BertuzziAuston MatthewsWilliam NylanderDougie HamiltonDarnell Nurse
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Wayne Simmonds, Mark Jankowski, Sam GagnerWayne Simmonds, Mark JankowskiWayne Simmonds
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Anton Stralman, Oliver Kylington, Brandon ManningAnton StralmanAnton Stralman, Oliver Kylington
Tirs de Pénalité
Auston Matthews, William Nylander, Tyler Bertuzzi, Nick Schmaltz, Wayne Simmonds
Gardien
#1 : Chris Driedger, #2 : John Gibson
Lignes d'Attaque Perso. en Prol.
Auston Matthews, William Nylander, Tyler Bertuzzi, Nick Schmaltz, Wayne Simmonds, Mark Jankowski, Mark Jankowski, Sam Gagner, Garrett Wilson, Owen Tippett, Vladimir Sobotka
Lignes de Défense Perso. en Prol.
Dougie Hamilton, Darnell Nurse, Adam Pelech, Anton Stralman, Oliver Kylington


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
LigueDomicileVisiteur
# 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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
00N/A0000000000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
000000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
000.00%000.00%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
00000000
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
000.00%000.00%000.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
000000


Derniers Match 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



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité60005000200040001000
Prix des Billets100603525200
Assistance0.00%0.00%0.00%0.00%0.00%
Attendance PCT0.00%0.00%0.00%0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
41 0 - 0.00%0$0$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
0$ 68,123,032$ 31,017,365$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0$ 23 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 8 0$ 0$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées Compte Bancaire Actuel Compte Bancaire Projeté
0$ 500,000,000$ 500,000,000$
Cap Salarial de la Saison ÉstiméCap Salarial DisponibleCap Salarial MaximumAu dessus du Plafond Salarial Minimum
0$ 81,500,000$ 81,500,000$ -60,200,000$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Tyler BertuzziAGE:24PO:0OV:69
Nick SchmaltzAGE:23PO:0OV:68
Mark JankowskiAGE:25PO:0OV:66
Sam GagnerAGE:30PO:0OV:64
Garrett WilsonAGE:28PO:0OV:64
Owen TippettAGE:20PO:0OV:64
Vladimir SobotkaAGE:32PO:0OV:64
Brian GibbonsAGE:31PO:0OV:62
Marko DanoAGE:24PO:0OV:62
Max McCormickAGE:27PO:0OV:62
Tye McGinnAGE:29PO:0OV:62
Joseph CramarossaAGE:26PO:0OV:59
Ryan BourqueAGE:28PO:0OV:59
Auston MatthewsAGE:22PO:0OV:75
Nick SchmaltzAGE:23PO:0OV:68
Mark JankowskiAGE:25PO:0OV:66
Sam GagnerAGE:30PO:0OV:64
Vladimir SobotkaAGE:32PO:0OV:64
Filip ChlapikAGE:22PO:0OV:62
Frederick GaudreauAGE:26PO:0OV:62
Lucas Elvenes (R)AGE:20PO:0OV:62
Brian GibbonsAGE:31PO:0OV:62
Alex BroadhurstAGE:26PO:0OV:61
Conner BleackleyAGE:23PO:0OV:60
Michael SpacekAGE:22PO:0OV:60
Brian PinhoAGE:24PO:0OV:59
Joseph CramarossaAGE:26PO:0OV:59
William NylanderAGE:23PO:0OV:70
Tyler BertuzziAGE:24PO:0OV:69
Nick SchmaltzAGE:23PO:0OV:68
Wayne SimmondsAGE:31PO:0OV:66
Sam GagnerAGE:30PO:0OV:64
Garrett WilsonAGE:28PO:0OV:64
Owen TippettAGE:20PO:0OV:64
Frederick GaudreauAGE:26PO:0OV:62
Brian GibbonsAGE:31PO:0OV:62
Michael SpacekAGE:22PO:0OV:60

Défense #1Défense #2Gardien
Dougie HamiltonAGE:26PO:0OV:73
Darnell NurseAGE:24PO:0OV:70
Adam PelechAGE:25PO:0OV:68
Anton StralmanAGE:33PO:0OV:68
Stephen JohnsAGE:27PO:0OV:66
Oliver KylingtonAGE:22PO:0OV:63
Brandon ManningAGE:29PO:0OV:61
Brennan MenellAGE:22PO:0OV:61
Mitch ReinkeAGE:23PO:0OV:61
Cody GoloubefAGE:29PO:0OV:59
Brett LernoutAGE:24PO:0OV:59
Michael PrapavessisAGE:28PO:0OV:58
Chad KrysAGE:21PO:0OV:57
Steven JohnsonAGE:25PO:0OV:57
John GibsonAGE:26PO:0OV:75
Chris DriedgerAGE:25PO:0OV:67
Adam WernerAGE:22PO:0OV:66
Richard BachmanAGE:32PO:0OV:64

Éspoirs

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
Éspoir Nom de l'ÉquipeAnnée de Repêchage Choix Total Information Lien
Aaron JohnsonRed Wings
Adam McQuaidRed WingsLien
Alex GrantRed Wings
Alexander SalakRed Wings
Alexandre PicardRed Wings
Andrew EbbettRed Wings
Andrew MillerRed Wings
Antoine VermetteRed Wings
Arthur KaliyevRed Wings924
Ben HolmstromRed WingsLien
Bobby SanguinettiRed WingsLien
Bracken KearnsRed Wings
Brad RichardsRed Wings
Brad RossRed Wings
Brett SterlingRed Wings
Cam WardRed WingsLien
Chris PhillipsRed Wings
Colby RobakRed Wings
Daniel WinnikRed Wings
Eric BaierRed Wings
Evan CowleyRed Wings
Evan ObergRed Wings
Filip KubaRed Wings
Henrik ZetterbergRed Wings
James GreenwayRed Wings697
Jay McClementRed Wings
Jean-Sebastien GiguereRed Wings
Jed OrtmeyerRed Wings
Jeff HalpernRed Wings
Jim SlaterRed Wings
John McCarronRed WingsLien
Josh GodfreyRed Wings
Justin FlorekRed Wings
Juuso ValimakiRed WingsLien
Kevan MillerRed WingsLien
Kyle MedvecRed Wings
Logan NelsonRed Wings2139
Marco CousineauRed Wings
Marcus DavidssonRed Wings757
Mark DekanichRed Wings
Matej PaulovicRed Wings3171
Matthew SpencerRed WingsLien
Mike WeaverRed Wings
Nikita FilatovRed Wings
PA ParenteauRed Wings
Patrik PuistolaRed Wings960
Radovan BondraRed Wings5110
Rod PelleyRed Wings
Roman CervenkaRed Wings
Ryan ButtonRed Wings
Ryan SuzukiRed Wings922
Sean B. CollinsRed Wings
Shane PintoRed Wings938
Stephane VeilleuxRed Wings
Stephen GiontaRed WingsLien
Stu BickelRed Wings
Theo PeckhamRed Wings
Trevor ZegrasRed Wings97
Ty SmithRed Wings811
Zachary LauzonRed Wings7112

Choix au Repêchage

Année R1R2R3R4R5R6
10
11
12
13
14






[2021-04-06 1:28:58 PM] - Red Wings didn't make playoff for year 9.
[2021-03-07 7:19:54 PM] - Wayne Simmonds was added to Red Wings.
[2021-03-07 7:19:54 PM] - Red Wings claimed Wayne Simmonds from waivers by Jets for $0.
[2021-03-07 7:19:40 PM] - Red Wings show interest in Wayne Simmonds from waiver.
[2021-03-02 8:58:52 PM] - TRADE : From Red Wings to Flyers : Kevin Hayes (73).
[2021-03-02 8:58:52 PM] - TRADE : From Flyers to Red Wings : Tyler Bertuzzi (69), Y:10-RND:4-DET.
[2020-11-25 7:45:07 PM] - TRADE : From Golden Knights to Red Wings : Stephen Johns (66), Mark Jankowski (66).
[2020-11-25 7:45:07 PM] - TRADE : From Red Wings to Golden Knights : Carter Verhaeghe (63), Y:10-RND:5-DET.
[2020-08-31 6:49:44 PM] - TRADE : From Kings to Red Wings : Steven Johnson (57), Michael Prapavessis (58), Joseph Cramarossa (59), Conner Bleackley (60), Brian Gibbons (62), Richard Bachman (64).
[2020-08-31 6:49:44 PM] - TRADE : From Red Wings to Kings : Y:12-RND:5-DET.
[2020-08-03 3:28:46 PM] - Adam Werner was added to Red Wings.
[2020-07-12 2:37:51 PM] - Red Wings drafts Patrik Puistola as the #60 overall pick in the Entry Draft of year 9.
[2020-07-12 2:23:01 PM] - TRADE : From Blue Jackets to Red Wings : Brett Lernout (59), Cody Goloubef (59), Tye McGinn (62), Ryan Bourque (59).
[2020-07-12 2:23:01 PM] - TRADE : From Red Wings to Blue Jackets : Y:11-RND:5-DET.
[2020-06-08 2:27:04 PM] - Lucas Elvenes was added to Red Wings.
[2020-06-08 2:19:46 PM] - Red Wings drafts Shane Pinto as the #38 overall pick in the Entry Draft of year 9.
[2020-06-04 6:52:18 PM] - Red Wings drafts Arthur Kaliyev as the #24 overall pick in the Entry Draft of year 9.
[2020-06-04 6:52:01 PM] - Red Wings drafts Ryan Suzuki as the #22 overall pick in the Entry Draft of year 9.



[2021-04-11 7:40:42 PM] Auto Lines Farm Function has been run for Griffins.
[2021-04-11 7:40:39 PM] Successfully loaded Red Wings lines done with Web Base Client and SQLite Database.
[2021-03-29 9:33:24 PM] Successfully loaded Red Wings lines done with Web Base Client and SQLite Database.
[2021-03-18 10:04:39 PM] Successfully loaded Red Wings lines done with Web Base Client and SQLite Database.
[2021-03-15 7:31:47 PM] Brian Gibbons(Red Wings) cleared from waivers and was sent to down farm.
[2021-03-14 10:04:10 PM] Successfully loaded Red Wings lines done with Web Base Client and SQLite Database.
[2021-03-14 10:04:10 PM] Brian Gibbons of Red Wings was sent down to farm.
[2021-03-14 10:04:08 PM] Red Wings placed Brian Gibbons on waivers.
[2021-03-13 11:20:18 PM] Successfully loaded Red Wings lines done with Web Base Client and SQLite Database.
[2021-03-10 9:26:31 PM] Nick Schmaltz from Red Wings is back from Right Foot Injury.
[2021-03-10 9:26:31 PM] Mark Jankowski from Red Wings is back from Broken Left Index Finger Injury.
[2021-03-10 9:26:31 PM] Game 1115 - Nick Schmaltz from Red Wings is injured (Right Foot) and is out for 1 days.
[2021-03-09 9:24:06 PM] Successfully loaded Red Wings lines done with STHS Client - 3.2.7.7
[2021-03-09 9:24:05 PM] Successfully loaded Red Wings lines done with Web Base Client and SQLite Database.
[2021-03-07 7:19:54 PM] Darnell Nurse from Red Wings is back from Torn Right ACL Injury.
[2021-03-07 7:19:54 PM] Wayne Simmonds was added to Red Wings.
[2021-03-07 7:19:54 PM] Red Wings claimed Wayne Simmonds from waivers by Jets for $0.
[2021-03-07 7:19:53 PM] Conner Bleackley from Griffins has scored a Hat Trick!
[2021-03-07 7:19:40 PM] Red Wings show interest in Wayne Simmonds from waiver.
[2021-03-06 7:44:10 PM] Successfully loaded Red Wings lines done with Web Base Client and SQLite Database.



Pas de Blessure ou de Suspension.


LigueDomicileVisiteur
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
28242260133725820949412313002121411132841191301125117962184258461719149777808270892388387358234567194217663567320.51%3685784.51%41588308151.54%1490290251.34%664132350.19%1994137219316111048525
3823523054692542342041191003225131116154116130224412311857025444569914917775182538844824815105219563184015813364713.99%3385783.14%21553293552.91%1440271353.08%663127552.00%2032141019346161052525
48236290346421920415412014022211089513411615012431111092722193775960797664716250079187580677224961168617392264218.58%2454382.45%21445284950.72%1371268751.02%615120850.91%1988138519476061049524
582223809814205239-3441151404413111121-10417240540194118-24442053695740270596611241079777281253230866572917102774415.88%2756476.73%21439285650.39%1410276750.96%640125051.20%2010139419126031050531
682362507923260235254120120252013310924411613054031271261722604787381687907412276188593090461251974559818283356017.91%2494980.32%11608304952.74%1477280752.62%647121553.25%206514811911577997507
7823533052522612322941161604131136118184119170112112511411702614567172486848114272084492891057252470063419332715821.40%2555180.00%41519297251.11%1441285050.56%647128550.35%2004141819395861031512
882273803545193217-244114180223295105-104113200131398112-14781933355286857616811206562369771065236070581718483224112.73%3685485.33%41346269349.98%1399280449.89%588119949.04%1937131919996181044517
882273803545193217-244114180223295105-104113200131398112-14781933355286857616811206562369771065236070581718483224112.73%3685485.33%41346269349.98%1399280449.89%588119949.04%1937131919996181044517
982194205844198271-73418210361289138-4941112102232109133-24681983545520377625011224774073374259239170868218833064013.07%2926079.45%51436281451.03%1392281049.54%616123749.80%1945134219936141049513
Total Saison Régulière73827929204148354320412058-17369149136022261818103910201936913015601922172510021038-36636204136105651174671963760911222014707073397282600212516141674516136275144616.21%275848982.27%28132802594251.19%128192514450.98%56681119150.65%179161244417569545293674675
Séries
240400000917-82020000047-320200000510-5091524001620135473344111504955851218.33%20670.00%17014747.62%7616446.34%277038.57%9260114335424
313670000034322615000001215-37520000022175123460940181691392112127121323751261842285259.62%51492.16%125349251.42%24547951.15%9419847.47%32722635410717988
4126600000414106420000020191624000002122-11241711120012151224211291721081238310099324421228.57%43979.07%023546150.98%18941845.22%10420351.23%2972082838615677
6106400000312925410000018144523000001315-212315182009146236899117120323701139528545920.00%37975.68%021241251.46%20742249.05%7215845.57%2681912587613468
Total Séries39182100000115119-419910000005455-120911000006164-33611519731201305129513163874493938712783884339221512717.88%1512881.46%2770151250.93%717148348.35%29762947.22%9866871010304524259