Detroit Red Wings

GP: 60 | W: 23 | L: 26 | OTL: 11 | P: 57
GF: 172 | GA: 198 | PP%: 25.21% | PK%: 75.76%
DG: Laurent Laporte | Morale : 21 | Moyenne d'Équipe : 75
Prochain matchs #927 vs Chicago Blackhawks
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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
1Patrick KaneXX100.00715589988797999860948885559492139850
2Jonathan Toews (C)X100.00795584889390849598878193559595139830
3William NylanderXX100.00675585967990929388908084558078130810
4Anthony ManthaXX100.00835582948687858960808583557476136790
5Andrew LaddX100.00955583849494868250757386559298126780
6Charlie CoyleXXX100.00925585899494898584837380557568136780
7Jean-Gabriel PageauXX100.00975589898686878287727490557674136770
8Carl SoderbergXXX100.00815589838383868279777689557578124760
9Daniel Sprong (R)X100.00665567796572706750626460557070133640
10Chris MuellerXX100.00605567687972706050606161557472135620
11Patrick Dwyer (R)X100.00625565616561655550555555556970137570
12Matt CareyXX100.00605569677566675550555556555050125570
13Seth JonesX100.00845591968796969725917697558179140860
14Ryan McDonaghX100.00815592919393979025866697558992136850
15Brent Seabrook (A)X100.00825586869687919125766789559490125820
16Brandon DavidsonX100.00915582858580787525636783558278125760
17Thomas Chabot (R)X100.00765593905582559125757289557775124750
18Andrej SustrX100.00665581799672827525636381558279120730
Rayé
MOYENNE D'ÉQUIPE100.0077558285838382815375718155797913175
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
1Tristan Jarry100.0078818485858579758084557875117790
2Anders Lindback (R)100.0070759279686470617387556562126700
Rayé
MOYENNE D'ÉQUIPE100.007478888277757568778655726912275
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Barry Trotz73848885927460CAN5554,300,000$


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'ÉquipePOS GP 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
1Patrick KaneDetroit Red WingsLW/RW60213960-1519540127252721848.33%12141923.6671421582200112963246.05%30400000.8526100232
2William NylanderDetroit Red WingsC/RW60242852-151610311311704911814.12%16122220.37101424402120002833250.58%86800010.8515020241
3Seth JonesDetroit Red WingsD60133649-22501012798129448310.08%84156226.0381725792270001174110.00%000000.6300101061
4Jonathan ToewsDetroit Red WingsC60242347-18355991522026313711.88%23137722.95915244622210141210258.10%170900100.6836100423
5Ryan McDonaghDetroit Red WingsD6083846-1844098789429618.51%114156226.0461824592270331175200.00%000000.5900000002
6Anthony ManthaDetroit Red WingsLW/RW60172845-2807194201501358.46%9107517.925712441880000254142.70%8900000.8403000333
7Charlie CoyleDetroit Red WingsC/LW/RW60142034-446012469129319710.85%7113918.99671327188000063048.38%67800000.6001000132
8Jean-Gabriel PageauDetroit Red WingsC/RW609253403001189816233885.56%10103917.32110113918811241491051.06%51700000.6500000030
9Brent SeabrookDetroit Red WingsD5952126-5551592596123508.20%88117119.86459291100001134000.00%000000.4400011200
10Andrew LaddDetroit Red WingsLW60111021-936010454101267210.89%1187914.66000150002531039.71%6800000.4801000021
11Carl SoderbergDetroit Red WingsC/LW/RW6010919-840178976205813.16%1577212.881011510111082247.35%50900000.4900000001
12Thomas ChabotDetroit Red WingsD5231417-741558475612315.36%5472613.98044176200019000.00%000000.4700010001
13Andrej SustrDetroit Red WingsD595813-8180422745143711.11%6197016.4422410840002110000.00%000000.2700000000
14Brandon DavidsonDetroit Red WingsD532911-8500123343717285.41%5786416.311341165000061000.00%000000.2500000000
15Daniel SprongDetroit Red WingsRW60202-521526131641112.50%268511.43000040000410037.21%8600000.0600001010
16Patrick DwyerDetroit Red WingsRW55101-1011527355220.00%23185.7900000000000018.18%1100000.0600001001
17Chris MuellerDetroit Red WingsC/RW40101-92051151520.00%12235.5900000000001043.20%16900000.0900000000
18Matt CareyDetroit Red WingsC/LW58011-12401598180.00%22844.9100000000020038.36%7300000.0700000000
19Jake DotchinGriffins (Det)D16011-4260339113100.00%1627817.41011442000022000.00%000000.0700000000
20Samuel MorinGriffins (Det)D10000100010100.00%0212.130000000004000.00%000000.0000000000
21Julien GauthierGriffins (Det)RW11000-220430100.00%1746.7800000000000035.71%4200000.0000000000
22Stuart PercyGriffins (Det)D7000300310000.00%17610.950000000001000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1080170310480-1775186012571207176049912159.66%5861774616.43601171774652058358211380211051.14%512300110.54622344142718
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
1Tristan JarryDetroit Red Wings48162090.8933.2327530414813890100.69213479701
2Anders LindbackDetroit Red Wings177620.8793.1485900453720100.600101347000
3Tyler ParsonsGriffins (Det)10000.9092.5024001110000.000004000
Stats d'équipe Total ou en Moyenne662326110.8913.2036370419417720200.652236060701


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Anders LindbackDetroit Red WingsG281988-05-02Yes216 Lbs6 ft6NoNoNo1Sans RestrictionPro & Farm500,000$500,000$129,944$No
Andrej SustrDetroit Red WingsD261990-11-28No220 Lbs6 ft7NoNoNo1Avec RestrictionPro & Farm1,000,000$1,000,000$259,887$No
Andrew LaddDetroit Red WingsLW311985-12-11No200 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm2,500,000$2,500,000$649,718$No
Anthony ManthaDetroit Red WingsLW/RW221994-09-15No214 Lbs6 ft5NoNoNo1Contrat d'EntréePro & Farm900,000$900,000$233,898$No
Brandon DavidsonDetroit Red WingsD251991-08-20No210 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$500,000$129,944$No
Brent SeabrookDetroit Red WingsD311985-04-19No220 Lbs6 ft3NoNoNo3Sans RestrictionPro & Farm5,000,000$5,000,000$1,299,435$No
Carl SoderbergDetroit Red WingsC/LW/RW311985-12-10No216 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm1,000,000$1,000,000$259,887$No
Charlie CoyleDetroit Red WingsC/LW/RW241992-03-02No221 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm3,500,000$3,500,000$909,605$No
Chris MuellerDetroit Red WingsC/RW301986-03-06No210 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm300,000$300,000$77,966$No
Daniel SprongDetroit Red WingsRW191997-03-17Yes181 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm900,000$900,000$233,898$No
Jean-Gabriel PageauDetroit Red WingsC/RW241992-11-11No175 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm3,500,000$3,500,000$909,605$No
Jonathan ToewsDetroit Red WingsC281988-04-29No201 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm6,500,000$6,500,000$1,689,266$No
Matt CareyDetroit Red WingsC/LW241992-02-27No195 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$300,000$77,966$No
Patrick DwyerDetroit Red WingsRW331983-06-21Yes175 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm300,000$300,000$77,966$No
Patrick KaneDetroit Red WingsLW/RW281988-11-18No177 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm8,000,000$8,000,000$2,079,096$No
Ryan McDonaghDetroit Red WingsD271989-06-12No213 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm5,000,000$5,000,000$1,299,435$No
Seth JonesDetroit Red WingsD221994-10-02No205 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm5,000,000$5,000,000$1,299,435$No
Thomas ChabotDetroit Red WingsD191997-01-30Yes190 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm900,000$900,000$233,898$No
Tristan JarryDetroit Red WingsG211995-04-29No194 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm500,000$500,000$129,944$No
William NylanderDetroit Red WingsC/RW201996-04-30No169 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm900,000$900,000$233,898$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2025.65200 Lbs6 ft22.202,350,000$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
47,000,000$38,600,000$15,500,000$5,900,000$0$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Patrick KaneJonathan ToewsWilliam Nylander40122
2Anthony ManthaCharlie CoyleJean-Gabriel Pageau30122
3Andrew LaddCarl SoderbergDaniel Sprong20122
4Matt CareyChris MuellerPatrick Dwyer10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth JonesRyan McDonagh40122
2Brent SeabrookBrandon Davidson30122
3Thomas ChabotAndrej Sustr20122
4Seth JonesRyan McDonagh10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Patrick KaneJonathan ToewsWilliam Nylander60122
2Anthony ManthaCharlie CoyleJean-Gabriel Pageau40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth JonesRyan McDonagh60122
2Brent SeabrookBrandon Davidson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Patrick KaneJonathan Toews60122
2William NylanderAnthony Mantha40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth JonesRyan McDonagh60122
2Brent SeabrookBrandon Davidson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Patrick Kane60122Seth JonesRyan McDonagh60122
2Jonathan Toews40122Brent SeabrookBrandon Davidson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Patrick KaneJonathan Toews60122
2William NylanderAnthony Mantha40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth JonesRyan McDonagh60122
2Brent SeabrookBrandon Davidson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Patrick KaneJonathan ToewsWilliam NylanderSeth JonesRyan McDonagh
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Patrick KaneJonathan ToewsWilliam NylanderSeth JonesRyan McDonagh
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Andrew Ladd, Carl Soderberg, Daniel SprongAndrew Ladd, Carl SoderbergDaniel Sprong
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Thomas Chabot, Andrej Sustr, Brent SeabrookThomas ChabotAndrej Sustr, Brent Seabrook
Tirs de Pénalité
Patrick Kane, Jonathan Toews, William Nylander, Anthony Mantha, Andrew Ladd
Gardien
#1 : Tristan Jarry, #2 : Anders Lindback


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
1Anaheim Ducks21100000660110000006421010000002-220.500611170021306722222305510204914321.43%4250.00%01081204852.78%1047206850.63%49295551.52%493544142512
2Boston Bruins31100001810-2110000005322010000137-430.500812200044018329262581013426588112.50%7271.43%21081204852.78%1047206850.63%49295551.52%735171223919
3Buffalo Sabres2110000069-31010000015-41100000054120.50061117001320498192205620105911327.27%5260.00%01081204852.78%1047206850.63%49295551.52%503745132412
4Calgary Flames2020000048-41010000003-31010000045-100.0004711002200562218160612025347228.57%10460.00%01081204852.78%1047206850.63%49295551.52%513542142612
5Carolina Hurricanes30100200411-71000010023-12010010028-620.3334812000130621522250992734739222.22%16381.25%01081204852.78%1047206850.63%49295551.52%704678223617
6Chicago Blackhawks11000000101000000000001100000010121.0001230100102510123018154234125.00%20100.00%01081204852.78%1047206850.63%49295551.52%2315247126
7Colorado Avalanche1010000005-51010000005-50000000000000.00000000000024911403111428400.00%20100.00%01081204852.78%1047206850.63%49295551.52%2214247126
8Columbus Blue Jackets311000101192210000109631010000023-140.667111627002441852422366983144626350.00%13284.62%01081204852.78%1047206850.63%49295551.52%694677223818
9Dallas Stars2020000038-51010000014-31010000024-200.000369001200401811110651736513133.33%9366.67%01081204852.78%1047206850.63%49295551.52%382557142411
10Edmonton Oilers2000010179-21000010034-11000000145-120.50071219003222582120156591312399333.33%60100.00%01081204852.78%1047206850.63%49295551.52%463251152713
11Florida Panthers3100101015782100001011471000100043161.0001526410037339633322587536205911436.36%7442.86%01081204852.78%1047206850.63%49295551.52%755372223820
12Los Angeles Kings2110000056-1110000004131010000015-420.50051015002210601220280561820398112.50%10460.00%01081204852.78%1047206850.63%49295551.52%523743132412
13Minnesota Wild1000010034-1000000000001000010034-110.50036900012028156705310222100.00%10100.00%01081204852.78%1047206850.63%49295551.52%2114276115
14Montreal Canadiens200010018801000000145-11000100043130.75081523004121631816277632216559222.22%8362.50%11081204852.78%1047206850.63%49295551.52%503655142211
15Nashville Predators2010010026-41000010023-11010000003-310.25024600020046614251501218359111.11%90100.00%01081204852.78%1047206850.63%49295551.52%432852162512
16New Jersey Devils2020000048-41010000013-21010000035-200.0004812000310441220120782520384125.00%100100.00%01081204852.78%1047206850.63%49295551.52%402756142310
17New York Islanders2010010048-41000010045-11010000003-310.2504812002110582319160522218299111.11%9455.56%01081204852.78%1047206850.63%49295551.52%513745132311
18New York Rangers1000000156-11000000156-10000000000010.500510150021202778962492214375.00%010.00%01081204852.78%1047206850.63%49295551.52%2922227127
19Ottawa Senators43100000171432110000079-222000000105560.750173047006830136474841010833298520630.00%11281.82%01081204852.78%1047206850.63%49295551.52%1007190294823
20Philadelphia Flyers312000001012-21010000023-12110000089-120.33310182800334011636374307827225518422.22%10190.00%01081204852.78%1047206850.63%49295551.52%765366213619
21Phoenix Coyotes1010000023-11010000023-10000000000000.00024600200017935037156244125.00%30100.00%01081204852.78%1047206850.63%49295551.52%2114267116
22Pittsburgh Penguins1010000012-1000000000001010000012-100.000123000100197660244415200.00%10100.00%01081204852.78%1047206850.63%49295551.52%2215246126
23St. Louis Blues1010000013-21010000013-20000000000000.0001120010003411121102010820200.00%4250.00%01081204852.78%1047206850.63%49295551.52%2618207137
24Tampa Bay Lightning2110000057-21010000025-31100000032120.5005914002210552221120682221407114.29%8275.00%01081204852.78%1047206850.63%49295551.52%493546132411
25Toronto Maple Leafs4400000021101122000000105522000000115681.00021396001710401675259560111424210216531.25%11281.82%01081204852.78%1047206850.63%49295551.52%1128178254927
Total60192602724172198-26301011005228998-9309150220283100-17570.475172310482045372438176056758458942177258651812572386025.21%1984875.76%31081204852.78%1047206850.63%49295551.52%146810321430432744374
27Vancouver Canucks2020000047-31010000013-21010000034-100.000471100112063211329070248366350.00%3166.67%01081204852.78%1047206850.63%49295551.52%493647132211
28Vegas Golden Knights11000000202110000002020000000000021.0002460101103212137028106216116.67%20100.00%01081204852.78%1047206850.63%49295551.52%2619217116
29Washington Capitals3120000056-1110000002022020000036-320.33359140104109431293407831215715320.00%8187.50%01081204852.78%1047206850.63%49295551.52%745267213718
30Winnipeg Jets210001008621000010023-11100000063330.750815230035005615251605616202812433.33%9366.67%01081204852.78%1047206850.63%49295551.52%473348152311
_Since Last GM Reset60192602724172198-26301011005228998-9309150220283100-17570.475172310482045372438176056758458942177258651812572386025.21%1984875.76%31081204852.78%1047206850.63%49295551.52%146810321430432744374
_Vs Conference38141402323124127-3187500222656232079021015965-6420.55312422134502365331611543643843893511133853298081493926.17%1242976.61%31081204852.78%1047206850.63%49295551.52%946669898272470238
_Vs Division201140201280651510530001140364106102001402911300.7508014222201273515564920922120823582209164458822226.83%571770.18%31081204852.78%1047206850.63%49295551.52%512366459142248127

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
6057L217231048217601772586518125704
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6019262724172198
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
30101105228998
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
30915220283100
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2386025.21%1984875.76%3
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
567584589425372438
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
1081204852.78%1047206850.63%49295551.52%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
146810321430432744374


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
2 - 2018-09-069Columbus Blue Jackets2Detroit Red Wings4WSommaire du Match
5 - 2018-09-0931Detroit Red Wings1Los Angeles Kings5LSommaire du Match
6 - 2018-09-1032Detroit Red Wings0Anaheim Ducks2LSommaire du Match
9 - 2018-09-1347Toronto Maple Leafs0Detroit Red Wings4WSommaire du Match
10 - 2018-09-1458Detroit Red Wings0Boston Bruins3LSommaire du Match
12 - 2018-09-1674Detroit Red Wings4Montreal Canadiens3WXSommaire du Match
15 - 2018-09-1996Detroit Red Wings3Tampa Bay Lightning2WSommaire du Match
17 - 2018-09-21105Detroit Red Wings4Florida Panthers3WXSommaire du Match
19 - 2018-09-23118Carolina Hurricanes3Detroit Red Wings2LXSommaire du Match
23 - 2018-09-27146Winnipeg Jets3Detroit Red Wings2LXSommaire du Match
25 - 2018-09-29162Dallas Stars4Detroit Red Wings1LSommaire du Match
27 - 2018-10-01171Detroit Red Wings2Columbus Blue Jackets3LSommaire du Match
29 - 2018-10-03181New Jersey Devils3Detroit Red Wings1LSommaire du Match
31 - 2018-10-05197Edmonton Oilers4Detroit Red Wings3LXSommaire du Match
34 - 2018-10-08216Vancouver Canucks3Detroit Red Wings1LSommaire du Match
37 - 2018-10-11237New York Rangers6Detroit Red Wings5LXXSommaire du Match
38 - 2018-10-12244Detroit Red Wings0Carolina Hurricanes5LSommaire du Match
41 - 2018-10-15265Phoenix Coyotes3Detroit Red Wings2LSommaire du Match
43 - 2018-10-17282Detroit Red Wings4Ottawa Senators3WSommaire du Match
45 - 2018-10-19296Detroit Red Wings3New Jersey Devils5LSommaire du Match
49 - 2018-10-23323Boston Bruins3Detroit Red Wings5WSommaire du Match
50 - 2018-10-24346Detroit Red Wings2Washington Capitals4LSommaire du Match
51 - 2018-10-25348Buffalo Sabres5Detroit Red Wings1LSommaire du Match
53 - 2018-10-27362Columbus Blue Jackets4Detroit Red Wings5WXXSommaire du Match
55 - 2018-10-29379St. Louis Blues3Detroit Red Wings1LSommaire du Match
58 - 2018-11-01396Detroit Red Wings3Boston Bruins4LXXSommaire du Match
59 - 2018-11-02408Colorado Avalanche5Detroit Red Wings0LSommaire du Match
61 - 2018-11-04418Tampa Bay Lightning5Detroit Red Wings2LSommaire du Match
63 - 2018-11-06437Detroit Red Wings6Toronto Maple Leafs2WSommaire du Match
65 - 2018-11-08449New York Islanders5Detroit Red Wings4LXSommaire du Match
67 - 2018-11-10461Los Angeles Kings1Detroit Red Wings4WSommaire du Match
68 - 2018-11-11474Detroit Red Wings1Washington Capitals2LSommaire du Match
71 - 2018-11-14489Ottawa Senators6Detroit Red Wings2LSommaire du Match
72 - 2018-11-15501Detroit Red Wings0New York Islanders3LSommaire du Match
75 - 2018-11-18526Detroit Red Wings6Philadelphia Flyers3WSommaire du Match
77 - 2018-11-20532Detroit Red Wings2Carolina Hurricanes3LXSommaire du Match
79 - 2018-11-22550Florida Panthers3Detroit Red Wings4WXXSommaire du Match
80 - 2018-11-23565Detroit Red Wings5Toronto Maple Leafs3WSommaire du Match
81 - 2018-11-24573Detroit Red Wings1Pittsburgh Penguins2LSommaire du Match
83 - 2018-11-26587Detroit Red Wings2Dallas Stars4LSommaire du Match
85 - 2018-11-28606Florida Panthers1Detroit Red Wings7WSommaire du Match
87 - 2018-11-30618Calgary Flames3Detroit Red Wings0LSommaire du Match
89 - 2018-12-02634Nashville Predators3Detroit Red Wings2LXSommaire du Match
91 - 2018-12-04647Washington Capitals0Detroit Red Wings2WSommaire du Match
93 - 2018-12-06659Montreal Canadiens5Detroit Red Wings4LXXSommaire du Match
96 - 2018-12-09686Detroit Red Wings6Winnipeg Jets3WSommaire du Match
97 - 2018-12-10692Detroit Red Wings3Minnesota Wild4LXSommaire du Match
100 - 2018-12-13713Anaheim Ducks4Detroit Red Wings6WSommaire du Match
103 - 2018-12-16736Detroit Red Wings4Calgary Flames5LSommaire du Match
105 - 2018-12-18755Detroit Red Wings3Vancouver Canucks4LSommaire du Match
107 - 2018-12-20762Detroit Red Wings4Edmonton Oilers5LXXSommaire du Match
113 - 2018-12-26784Toronto Maple Leafs5Detroit Red Wings6WSommaire du Match
114 - 2018-12-27797Detroit Red Wings6Ottawa Senators2WSommaire du Match
119 - 2019-01-01827Vegas Golden Knights0Detroit Red Wings2WSommaire du Match
121 - 2019-01-03840Detroit Red Wings5Buffalo Sabres4WSommaire du Match
122 - 2019-01-04854Detroit Red Wings1Chicago Blackhawks0WSommaire du Match
124 - 2019-01-06869Detroit Red Wings0Nashville Predators3LSommaire du Match
126 - 2019-01-08880Ottawa Senators3Detroit Red Wings5WSommaire du Match
128 - 2019-01-10898Detroit Red Wings2Philadelphia Flyers6LSommaire du Match
129 - 2019-01-11905Philadelphia Flyers3Detroit Red Wings2LSommaire du Match
132 - 2019-01-14927Chicago Blackhawks-Detroit Red Wings-
134 - 2019-01-16942Minnesota Wild-Detroit Red Wings-
136 - 2019-01-18958San Jose Sharks-Detroit Red Wings-
138 - 2019-01-20972Montreal Canadiens-Detroit Red Wings-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
142 - 2019-01-24999Detroit Red Wings-Phoenix Coyotes-
145 - 2019-01-271021Detroit Red Wings-Colorado Avalanche-
147 - 2019-01-291037New York Rangers-Detroit Red Wings-
149 - 2019-01-311058Detroit Red Wings-Tampa Bay Lightning-
150 - 2019-02-011062Detroit Red Wings-Florida Panthers-
152 - 2019-02-031076Detroit Red Wings-Montreal Canadiens-
154 - 2019-02-051085Tampa Bay Lightning-Detroit Red Wings-
156 - 2019-02-071102New York Islanders-Detroit Red Wings-
159 - 2019-02-101129Detroit Red Wings-New York Rangers-
161 - 2019-02-121146Detroit Red Wings-St. Louis Blues-
163 - 2019-02-141162Detroit Red Wings-Vegas Golden Knights-
165 - 2019-02-161173Detroit Red Wings-San Jose Sharks-
168 - 2019-02-191189Detroit Red Wings-Buffalo Sabres-
169 - 2019-02-201199New Jersey Devils-Detroit Red Wings-
171 - 2019-02-221217Boston Bruins-Detroit Red Wings-
173 - 2019-02-241234Pittsburgh Penguins-Detroit Red Wings-
175 - 2019-02-261249Detroit Red Wings-Pittsburgh Penguins-
177 - 2019-02-281261Buffalo Sabres-Detroit Red Wings-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité de l'Aréna60005000200040001000
Prix des Billets100603520200
Assistance167,945138,45855,336111,31527,429
Attendance PCT93.30%92.31%92.23%92.76%91.43%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
11 16683 - 92.68% 1,042,525$31,275,755$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
38,551,999$ 47,000,000$ 27,494,000$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
47,000,000$ 35,329,376$ 0$ 20 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
11,467,777$ 46 289,831$ 13,332,226$

Total de l'Équipe Éstimé
Dépenses de la Saison ÉstiméesCap Salarial de la Saison ÉstiméCompte Bancaire ActuelCompte Bancaire Projeté
13,966,132$ 47,000,000$ 130,192,314$ 127,693,959$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Patrick KaneAGE:28PO:1OV:85
Anthony ManthaAGE:22PO:1OV:79
Andrew LaddAGE:31PO:1OV:78
Charlie CoyleAGE:24PO:1OV:78
Carl SoderbergAGE:31PO:1OV:76
*Trevor MooreAGE:21PO:1OV:58
Matt CareyAGE:24PO:1OV:57
Jonathan ToewsAGE:28PO:1OV:83
William NylanderAGE:20PO:1OV:81
Charlie CoyleAGE:24PO:1OV:78
Jean-Gabriel PageauAGE:24PO:1OV:77
Carl SoderbergAGE:31PO:1OV:76
Chris MuellerAGE:30PO:1OV:62
Dominic TurgeonAGE:20PO:1OV:59
Cole CasselsAGE:21PO:1OV:58
*Trevor MooreAGE:21PO:1OV:58
Matt CareyAGE:24PO:1OV:57
Kyle PlatzerAGE:21PO:1OV:56
Patrick BrownAGE:24PO:1OV:53
Patrick KaneAGE:28PO:1OV:85
William NylanderAGE:20PO:1OV:81
Anthony ManthaAGE:22PO:1OV:79
Charlie CoyleAGE:24PO:1OV:78
Jean-Gabriel PageauAGE:24PO:1OV:77
Carl SoderbergAGE:31PO:1OV:76
*Daniel SprongAGE:19PO:1OV:64
Chris MuellerAGE:30PO:1OV:62
*Patrick DwyerAGE:33PO:1OV:57
Kyle PlatzerAGE:21PO:1OV:56
Patrick BrownAGE:24PO:1OV:53
*Julien GauthierAGE:19PO:1OV:52

Défense #1Défense #2Gardien
Seth JonesAGE:22PO:1OV:86
Ryan McDonaghAGE:27PO:1OV:85
Brent SeabrookAGE:31PO:1OV:82
Brandon DavidsonAGE:25PO:1OV:76
*Thomas ChabotAGE:19PO:1OV:75
Jake DotchinAGE:22PO:1OV:75
Andrej SustrAGE:26PO:1OV:73
Samuel MorinAGE:21PO:1OV:63
Stuart PercyAGE:23PO:1OV:55
Jonathan RacineAGE:23PO:1OV:54
*Jakub ZborilAGE:19PO:1OV:54
Tristan JarryAGE:21PO:1OV:79
*Anders LindbackAGE:28PO:1OV:70
*Tyler ParsonsAGE:19PO:1OV:53

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
Adam KubikDetroit Red Wings13180
Axel Jonsson-FjallbyDetroit Red Wings12170
Dmitry ZhukenovDetroit Red Wings11119
Gabriel VilardiDetroit Red Wings135
Jack StudnickaDetroit Red Wings1347
Jakub GalvasDetroit Red Wings13160
Jaret Anderson-DolanDetroit Red Wings1334
Jason RobertsonDetroit Red Wings1336
Jeremy SwaymanDetroit Red Wings1398
Lucas ElvenesDetroit Red Wings1367
Radovan BondraDetroit Red Wings11149
Stelio MattheosDetroit Red Wings1358
Tobias GeisserDetroit Red Wings13129
William LagessonDetroit Red Wings10124

Choix au Repêchage

Année R1R2R3R4R5R6
14Det Det Buf Phi Det PHX Det Det Det
15Det STL Det Tam Det Det Det NYI Det
16Det Det Det Clb Det Det Det
17Det Det Det Det Det Det
18Det Det Det Det Det Det



[2018-12-03 18:11:22] - TRADE : From Boston Bruins to Detroit Red Wings : Y:15-RND:2-Tam.
[2018-09-29 10:54:34] - Team Name Change : Grand Rapids Griffins changed name to Griffins
[2018-09-14 09:54:32] - TRADE : From New York Islanders to Detroit Red Wings : Y:15-RND:1-STL, Y:16-RND:3-Clb.
[2018-09-14 09:54:32] - TRADE : From Detroit Red Wings to New York Islanders : Henrik Lundqvist.
[2018-09-09 07:39:55] - Grand Rapids Griffins hired Adam Oates for 1 900 000 $ for 3 year(s).



[2019-02-03 22:03:56] Last 7 Days Pro Star : 1 - Anders Lee of Nashville Predators (4-4-8) / 2 - Andre Burakovsky of Toronto Maple Leafs (5-4-9) / 3 - Charlie Coyle of Detroit Red Wings (2-7-9)
[2019-01-28 18:06:48] Andrej Sustr from Detroit Red Wings is back from Bruised Left Leg Injury.
[2019-01-28 18:06:47] Game 784 - Andrej Sustr from Detroit Red Wings is injured (Bruised Left Leg) and is out for 1 days.
[2019-01-25 15:39:52] Tyler Parsons from Griffins is back from Exhaustion.
[2019-01-24 17:31:24] Tyler Parsons from Griffins injured (Exhaustion)



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
1360192602724172198-26301011005228998-9309150220283100-1757172310482045372438176056758458942177258651812572386025.21%1984875.76%31081204852.78%1047206850.63%49295551.52%146810321430432744374
Total Saison Régulière60192602724172198-26301011005228998-9309150220283100-1757172310482045372438176056758458942177258651812572386025.21%1984875.76%31081204852.78%1047206850.63%49295551.52%146810321430432744374